Approximate min-max relations on plane graphs Let G be a plane graph, let ?(G) (resp. ??(G)) be the minimum number of vertices (resp. edges) that meet all cycles of G, and let ?(G) (resp. ??(G)) be the maximum number of vertex-disjoint (resp. edge-disjoint) cycles in G. In this note we show that ?(G)?3?(G) and ??(G)?4??(G)?1; our proofs are constructive, which yield polynomial-time algorithms for finding corresponding objects with the desired properties. Graphs considered in this note are finite and simple. Let G = (V , E) be a graph (undirected or directed). A subset X of V (resp. E) is called a feedback vertex (resp. edge) set if X intersects every cycle in G. (As usual, by a cycle in a directed graph we mean a directed one.) Let τ (G) (resp. τ (G) ) be the minimum size of a feedback vertex (resp. edge) set of G, and let ν(G) (resp. ν (G)) be the maximum number of vertexdisjoint (resp. edge-disjoint) cycles in G. Clearly, ν(G) ≤ τ (G) and ν (G) ≤ τ (G); these inequalities, however, need not hold equalities in general. Thus a natural question to ask is: How large can τ (G)/ν(G) and τ (G)/ν (G) be? As shown by Erdős and Pósa (1965) In this note we have established two approximate min-max relations on packing and covering cycles in plane graphs. We remark that the assertion of Theorem 1 actually holds for any graph G that can be 2-cell embedded in the projective plane, torus, and Klein bottle. To justify this, we need to establish a counterpart of Lemma 1 for a graph G on these surfaces. It can be shown using a discharging method that if G is 2-cell embedded in the projective plane, then Lemma 1 remains true; if G is 2-cell embedded in the torus or the Klein bottle, then one of the following four cases occurs: The remainder of the proof goes along the same line as that of Theorem 1. Despite our effort, the Kloks-Lee-Liu conjecture remains unsolved. To demonstrate the difficulty of this type of problems, let us take a second look at the proof of Theorem 2: Is it possible to produce a proof without using the 4-color theorem (4CT)? Such a proof is very hard to obtain, if not impossible. In fact, a long-standing open problem in graph theory posed by Erdős is to find a 4CT-free proof of the statement: Every n-vertex plane graph contains an independent set of size at least n/4. We point out that the Král-Voss theorem stated in Sect. 1 resembles Theorem 2 in nature, whose proofs (Král and Voss 2004; Fiorini et al. 2007 ) also rely heavily on the 4CT. We conclude this note by another closely related, innocently looking, yet frustrating conjecture made by Albertson and Berman (1979) : Every n-vertex plane graph has a feedback vertex set of size at most n/2.

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Play-it-by-eye! Collect movies and improvise perspectives with tangible video objects We present an alternative video-making framework for children with tools that integrate video capture with movie production. We propose different forms of interaction with physical artifacts to capture storytelling. Play interactions as input to video editing systems assuage the interface complexities of film construction in commercial software. We aim to motivate young users in telling their stories, extracting meaning from their experiences by capturing supporting video to accompany their stories, and driving reflection on the outcomes of their movies. We report on our design process over the course of four research projects that span from a graphical user interface to a physical instantiation of video. We interface the digital and physical realms using tangible metaphors for digital data, providing a spontaneous and collaborative approach to video composition. We evaluate our systems during observations with 4-to 14-year-old users and analyze their different approaches to capturing, collecting, editing, and performing visual and sound clips. From an early age, we play, learn, and exchange ideas about our identity using stories; we test our hypotheses by playing with toys, telling stories, and acting in the world. Today, communications technology expands our resources for exploring and sharing our reflections on the environment we live in. With mobile technology, we enter a creative and collaborative world where images, sound, and language mix. Shared movie-making devices can engage people in multidimensional approaches to expressing and exchanging points of view. We imagine a world in which, through play, children create and exchange visual narratives about their lives and their environment.. We connect to our world using our senses. Each sense is a "knowledge shopper" that grounds us in our surroundings (Ackermann, 1990) : with touch, we feel the texture of life; with hearing, we perceive even the subtlest murmurs of our existence; with vision, we clarify our instincts. We use gesture to apprehend, comprehend, and communicate. We speak to exchange with others. We visualize, record, and play back events using memory to reflect on our history and to immerse ourselves in experience. We engage in everyday pretense and symbolic play. We embed and later withdraw from the world, using imagination to project ourselves into situations (Singer & Singer, 1990) .. Children are offered stories by adults and are driven into fantasy play. They use toys to externalize and elaborate their mental constructions (Fein, 1979) . Oral stories in children's play make use of linguistic structure (quoted speech, direct speech, narrator voice) and context (providing spatial and temporal expressions in stories); children's ability to use language to communicate when and where their story takes place is considered a milestone in literacy development (Snow, 1983) .. Constructionist educators have demonstrated that young users benefit from systems that support self-expression, because children "learn by making" (Harel & Papert, 1991; Resnick, 2002; Ackermann, 1996 Ackermann, , 2004 . Still, most commercial technological toys do not provide space for children to tell their own stories; rather, the toys tell stories to the children. Video composition tools could support children's authorship; however, the interaction paradigm in traditional video editing systems is a time line; the objective is to make an immutable "final" cut of a movie. The author can only see the whole once she renders the time line. Now, with digital video, we can change the video-making process so that children can easily use video as an expressive composition tool.. Toys initiate elaboration in play and language. Researchers have found a correlation between open-ended play and imagination in writers, poets, and scientists (Singer & Singer, 1990) . The 18th century German writer Goethe reported treasuring the puppet theater he had as a child as he envisioned relationships and plots between characters in his later novels. Toys and storytelling serve a fundamental function in childhood development (Montessori, 1912; Singer & Singer, 1990; Brosterman, 1997) , and the ability to move from one's own standpoint to take another person's view in a story is at the center of cognitive growth (Piaget & Inhelder, 1967; Winnicott, 1971; Ackermann, 1996) . "Dwelling in" and "stepping back" are equally important to get the cognitive dance going (Ackermann, 2004) ; when a child makes a movie, shedwells inas she creates and tells her story andsteps back as she watches the movie she just made. However, creating movies requires media composition and narrative skills, which existing user interfaces scaffold poorly for novice users and children (Landry, 2008) .. Through design we seek to understand how tangible interfaces for composing movies can empower young users in expressing and sharing ideas, actively "constructing" personal movies driven by storytelling. Indeed, "Children build, make or manipulate objects or artifacts and in doing so are confronted with the results of their actions, learning as they go" (Harel & Papert, 1991) . Movie editing systems support personal creation and offer opportunities to convey and reflect on "real-world" experiences. Cell phones, video cameras, and computer game consoles could serve as vehicles for manipulating personal media to co-construct video games, movies, and songs. We base our design exploration on a language of interaction that children are familiar with, adopting play interactions to control a video editing system. The goal is to assuage the interface complexities of commercially available editing software. We aim to motivate young users in telling their stories, extracting meaning from their experiences by capturing video elements to accompany their stories, and driving introspective reflection. We have described four design iterations of a tangible video editing system for children. We began with preliminary workshops, where we found that most children preferred recording a video to editing with commercial software. To motivate children to make a movie from beginning to end and to remain focused during video editing we designed strategies for interacting with media content. Our strategies strike a compromise between the powerful capabilities of commercial editing software and the goal of engaging children in making video.. Our first design iteration, Textable Movie, avoids the technical difficulties of commercial editing video software by coupling the task of editing a movie with the performative act of telling a story. Our evaluation of Textable Movie suggested a framework for video editing and storytelling, motivated by playful improvisational storytelling. So in Moving Pictures we aimed to interface video capture, editing and publication, using a tangible element to view, revisit, share, and collaborate on video sequences. Moving Pictures helped children improvise and perform movies collaboratively. Using tokens to retrieve video clips focuses children on editing so they follow their original vision from capturing to editing a final movie. Children are familiar with playing with toys, play-acting character discussions, and enacting toy interrelationships and stories, so in Terraria we used toys to focus children's attention on video composition. Creating video with toys and a game controller, we place children in a familiar realm. The results were pronounced: children spent hours creating, editing, performing movies with the robot toy performers, and projecting their pieces. However, one important component was still missing: children did not tell stories; instead, they merely assembled visual scenes. By combining improvisation with movie making during play, Picture This! extends play to creative outcomes. Automating editing with gesture object interaction allows a child to focus on an object in a captured scene, for instance, a specific character. The video-making process, supported by gesture-induced editing, helps children practice social relationships and take visual perspectives, expanding creative storytelling in video composition.. These design iterations facilitate movie making and engage children in editing a final piece. Except for iMovie and Textable Movie, which do not include an integrated system to capture movies, all our systems offered the following modes of interaction: capturing, editing, performing/playback, composing a final movie, conducting storytelling from the firstperson perspective, and storytelling using a narrator voice.. We have synthesized our observations of children's interactions (aged 8-14) with our four movie-making systems and the iMovie video editing system (see Table 1 ).. Compared with commercial video editing systems such as iMovie, our systems enable children to embed their stories in movies, or to drive their movies by telling stories (in both Textable Movie and Picture This!). Given a choice between an interactive visual storytelling system and the powerful iMovie video editing software, fewer than 50% of the children chose to play back their movies with iMovie. For both Textable Movie and iMovie, fewer than 50% exported a final movie. All the other systems engaged more than 80% of the children to create and play back a movie. We expected children to conduct storytelling with Terraria using their toys, but fewer than 50% did so, and they used the system only to assemble videos and add visual and audio effects. Terraria did not support storytelling; however, this technology required the least instruction. Children did not narrate when recording with Moving Pictures and iMovie, which would have provided an oral context (spatial and temporal) to their visual stories. While interacting with Textable Movie and Picture This!, participants told stories both from first-person and narrator perspectives. Even though Picture This! was designed to drive movie making by conversational storytelling between toys, children older than 8 years spontaneously integrated a narrator. Implemented sequentially, we learned from each iteration as we moved from a computer-screen-keyboard to a gesture-object-based interface for video expression.. We presented our video-making framework, motivated by the playful improvisational environment of storytelling and integrating tangible technology into video editing systems in the form of toys. We stated the need for a new category of video-editing tools leveraging the child's natural expression of play. Tangible editing systems can engage children in an entirely new video making activity, gaining visual perspectives, driving play, and expanding discovery of their environment. In our tangible movie-making systems, children create story content for editing and performance, and they learn to make a movie "as they go on with their storytelling." With our four iterations of movie-making devices, we redressed a limitation in commercially available video editing software by motivating children to create a final piece. By successfully completing a movie, children can then reflect on the finished piece. To collect videos, we asked participants to be reporters of their city. The children captured media clips to represent their environment. They were motivated to capture movies, and they respected the content of their storyboard. However, during the editing phase, we lost their attention. When asked to edit their movie to create a final movie in iMovie, more than half of the children stated they preferred continuing the capture process. However, when children were asked to segment and label video segments for the Textable Movie software, they attentively created mappings between text and images. They also composed creative interactions by associating videos with humorous keywords. During the projection phase, they collaboratively created an interactive movie by shouting keywords to type in. The computer keyboard appeared to limit collaborative video making, because only one user at a time could enter the commands offered by the group. The children explored their collective video database, revisiting their keyword matching and recreating video clips as needed. The digitizing and editing phase is necessary for the children to clean their raw data, clarify their video expression and select pieces for use with Textable Movie. If they dropped out of one of these phases, their original vision, as presented in their storyboard, was not followed, and the children did not produce a movie that they were satisfied with.. Observing the creative process of the children working on digital media with Moving Pictures, we found that they exhibited the four aspects of Understanding of the Arts proposed by Ross and reintroduced by Somers (2000) : conventionalization, an awareness and ability to use the conventions of the art form; appropriation , embracing, for personal use, the available expressive forms; transformation, the search for knowledge and meaning through the expression of "feeling impulses;" and publication, placing the result in the public domain. Using Moving Pictures, children made a movie using a series of traditional shots symbolized by physical tokens. They respected their storyboard and they contributed to a video database by expressing their visual narratives for another group of children. Video-jockeying is a spontaneous way to perform final pieces and to integrate selected sounds. It became the physical translation of the projectionist in Textable Movie. Children were engaged in producing all the video stories they created from initial capture to editing their final pieces. Having the digital data represented by physical objects helped the children understand the construction of their movies. Moving Pictures succeeded in engaging children in the entire movie-making process. However, it lacked scaffolding from the children's oral storytelling.. Children were drawn to give a visual life to their robotic toys. They spent an average of 1 h playing with the robots, recording movies about them and projecting the movie. The exhibition curator reported that the system was a success and by far the most visited and played with exhibit at the museum. The simplicity of use and immediacy of response seemed to engage visitors in creating movies. Both during our user studies and during the exhibition, users recorded videos, and selected soundtracks to fit with their videos and to unify their composition.. Although we have not performed a controlled study to validate our qualitative observations, Picture This! seems to allow children to capture storytelling with physical artifacts at different levels of interaction. Functionalities and mode of interaction could be distinguished with a specific cognitive goal for each age group. For children under 6 years old, Picture This! functions as a video performance system with video snippets of the child's play, with only one of the two toys carrying a camera. The preview seems to help them develop spatial-visual coordination while playing with their favorite toys and telling stories. Picture This! allows older children to test visual angles and assemble a movie as they play with their toys and tell stories alternating between direct speech and narrator voice, providing spatial and temporal context. The recording and playback modes seem to enable older children to use their social perspective taking visually and through storytelling.. The youngest children (under 8 years old) transferred their personal characteristics into the toys. For instance, a doll dances because the child takes dancing lessons. Or a doll takes her first picture, because this is the first time the child takes a picture herself. Another child shakes the doll while saying: "Shake! Shake! I want to be in the camera!" and she shakes her own body. Older children (over 8 years old) talked to the dolls, giving directions for the movie. A child brought a doll to her face, as if the doll had a mind of its own, to say, "You don't carry your wand like that. You don't put the wand at people like that!" Children navigate from transferring their own lives onto their toys and attributing human characteristics to the toys. All the children in our evaluation developed spontaneous conversations between the character toys, testing their social knowledge and perspective taking. The following is an excerpt of a video story by Jeremy, 10 years old (see Fig. 7 for missing dialogue):. D1: "Hi! My name is Fred what's yours?" . . . D1: "Over there in the great yellow mountains, but there is a giant blocking the way. We need to take down the giant so that we can find the treasure." D2: "sounds good to me, when do you wanna go?" D1: "how about right now?" D2: "ok let's go" Narrator voice: and they walked off to the mountains to destroy the giant and get the Peruvian treasure. D1: "tutututututut" (walking the dolls though the yellow mountains.) Then in front of the giant, the child says with the doll in the video frame: D2: "hey you evil sid cops, surrender! Face the rest of us! We are superior and strong! We shall take you down!" Then the child uses one of the two dolls to take a video of the giant and says (taking the voice of the giant) Giant: "I shall take you down first, face the rest of me!" Playing with video character toys in Picture This! allows children to develop visual perspective taking skills. This entails, for example, determining where objects are located relative to another agent, or whether the agent can see a particular object (Michelon & Zacks, 2006) . The high level of concentration the children exhibited demonstrates how challenging it is to find the right angle and distance between the object and the camera, and between the two objects. Textable Movie, our first design prototype, was intentionally not tangible. Rather, it was intended to inform the design of later tangible platforms for making movies. We wanted to provide an alternative to commercially available video editing software, allowing improvisation and unexpected discovery of media content and to make visual storytelling more playful, engaging, and powerful for young people (Resnick, 2006) . Our previous research led to the idea that the projectionist, viewer, and maker could use text input to sequence the projection (Vaucelle et. al, 2003) . However, early testing uncovered a basic limitation: how would the projectionist/ viewer know what words to use? Our response in Textable Movie is that players submit and name their own images.. Based on our experience with Textable Movie, and with children as design partners, we implemented a tangible movie making system. This self-contained platform offers children the opportunity to collect video clips from their environment and later compose video using an editing station that provides tangible access to their entire media collection. We aimed to motivate the children to explore the entire process of making a movie. We originally designed Moving Pictures for users aged 10-14. However, because the interaction relies exclusively on manipulating tokens, children as young as 4 years old can play with the system and interact with video clips. To accommodate various age groups and individual characteristics of users, we integrated different layers of complexity, from digitizing the media, performing a movie, to storyboarding a more complex narrative, similar to the video-making process during the Textable Movie workshop.. Computer game controllers, for example, joysticks, can serve to manipulate personal media. We hypothesized that because of children's familiarity with their everyday toys and games, children could be drawn into video making with a joystick. Our next design iteration,Terraria , employed a joystick for video capturing, editing, and performing. The joystick controls camera angles, recording, video and sound effects, playback, and projection of the final movie onto a screen.

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Incremental Scenario Modeling Using Hierarchical Object-Oriented Petri Net Scenario-based modeling is emerging as a key technology in software development because scenarios are easy to describe and understand, naturally describing the real world, and highly used in several development phases. Scenario-Based Software Modeling(SBSM) represents scenarios with a formal method, and then integrates each scenario into a global one excluding redundant, incomplete, and inconsistent elements. An issue which is not yet proposed a clear solution in SBSM is the handling of di erent abstraction levels. In the existing proposals, this problem is hidden with an implicit assumption that all such scenarios have the same abstraction levels, which w e believe to be unrealistic. In our research, we propose a Hierarchical Object-Oriented Petri Net(HOONet) as a method to specify the scenarios, and also suggest a method to integrate scenarios including di erent abstraction levels as well as redundancy, incompleteness, and inconsistency. Coordinating abstraction levels of scenarios can be achieved by considering scenario models as state-based transition models and verifying the transition models in respect to behavioral equivalence. In order to show the e ectiveness of our suggestion, overall processes of SBSM using HOONet are explained with a practical example. Software modeling based on scenarios is a widely used method in the development o f i n d u s t r i a l a pplications because the method can naturally represent user requirements and drive user's attending in requirements analysis work. Scenarios are the description of requirements representing the interaction between system and actors, and they provide the multiple views in the several aspects of the system 7, 1 3 ] .. The main problems in the scenario-based software modeling process are incompleteness caused by insu cient scenarios for the whole system behaviors, and inconsistency caused by redundant and/or overlapping scenarios for the same behavior. To cover these problems, the scenarios described by natural language are transformed into formal representations, and then the transformed scenarios are integrated into a global scenario. In this process, the incompleteness and inconsistency problems can beavoided by the veri cation techniques of formal methods 16, 23, 2 7 ] .. However, scenarios can represent di erent views of a system and can be described with di erent abstractions because they are elicited from multiple views of various users. These scenarios should be integrated into a global scenario after coordinating the di erent abstraction levels of each scenario to an equivalent level. However, existing researches on scenario integration have the strict assumption that each scenario has the same abstraction level. This assumption is not realistic. Rolland 24] and Desharnais 9] speci cally pointed out that the abstraction problem must be solved in scenario-based software modeling.. In this paper, we suggest a modeling method of system requirements based on scenarios, which introduces an object-oriented formal technique to coordinate the di erent abstraction levels of scenarios. Our method, HOONet(Hierarchical Object-Oriented Petri Net) adopts object-oriented concepts to support the hierarchical abstractions and Petri net formalism to formally represent scenarios. The HOONet method can model the di erent abstraction levels of system states and behaviors, and is able to incrementally perform the modeling and analyzing when the abstraction is not fully re ned yet. Because HOONet models can be analyzed by the incremental and compositional approach, this approach a l l o ws us to reduce the state explosion problem which can occur in the analysis of integrated scenario models.. This paper is organized as follows: In Section 2, we brie y review some of the earlier proposals made for scenario-based modeling and identify their shortcomings. In Section 3, we rst give some consideration issues for scenario modeling, and justify a need for de ning HOONet by explaining what is required to accomplish our goal. We provide an informal and intuitive introduction to HOONet as well as formal de nitions. Section 4 describes a systematic procedure for modeling a system using HOONet, and explains the procedure through modeling an example system represented with abstract information. Integrating scenarios and coordinating their abstraction levels are explained in Section 5. In Section 6, analysis techniques for ensuring the correctness of structural and behavioral properties in HOONet models are discussed. We provide the algorithms to generate a reachability graph of HOONet models. Section 7 concludes our paper and suggests further research issues. In Appendix A and B, the detail descriptions of HOONet formalism are given. In software and system engineering areas, management of scenarios is emerging as a useful technology for specifying, modeling, testing a system, and managing the change of system information. Practically, research and applications of scenario management h a ve been done in CREWS, ESPRIT projects 1].. Our paper focuses on providing the solutions of two problems which can appear in the process of scenario-based modeling of complex and large-scale systems One is how the di erent abstraction levels of a behavior included in multiple scenarios are coordinated, and the other is the possibility of modeling the system requirements that are not fully analyzed yet. To solve these problems, we suggested HOONet which is an object-oriented high-level Petri net and the modeling procedures of a system using HOONet. In the process of scenario integration, we also suggest the ways of identifying the replicated and missed parts of system behaviors, coordinating the di erent abstraction levels of behaviors and analyzing the reachability of HOONet models using incremental approach.. Our results can provide the adequate representation of system behaviors as well as the completeness and consistency of scenarios integration. Especially, the HOONet method copes with the di culties of the two issues mentioned above -abstraction level coordination and incremental modeling and analysis, which have n o t been handled in the existing proposals. We believe that these results can contribute for the modeling and analyzing a system using scenarios in large and complex industrial applications.. While our research o ers those improvements mentioned above, in the scenario-based software modeling, there are some issues that are worthy of further research. First, software tools to support HOONet method are needed because the productivity gains are limited when applying our method manually. Thus, we a r e n o w developing the HOONet tools using V i s u a l C a f e T M and J a v a language.. Second, HOONet formalism itself could be extended. The area for the extension will include the support for timing analysis. Finally, applying the HOONet formalism to various software engineering domains can be studied. Reuse of the HOONet models and change management of requirements will become other research domains where our HOONet formalism can show its ability.. De nition of Transitions: A set of transitions in HOONet, T = fT i T a T c g, w h e r e Static reactions of Pa T a, a n d Tc Pa(place name) = f(condition of ag variables) : post conditionsg Ta(transition name) = f(condition of ag variables) : post conditionsg Tc(transition name) = f(condition of ag variables) : post conditionsg { condition of ag variables j post conditions = boolean-expression. In the de nition above, the notation \+" menas that the declaration can be globally referenced. The \with" phrase is to represent t h e constraints imposed to primitive type of token, for example, \integer with 1..100]". Recently, the existing researches on scenario-based software engineering have focused on scenario integration to represent t h e global behavior of a system 10, 16, 1 7 , 28] . Our research, on the other hand, focuses on the handling of the di erent abstraction levels in the scenario integration. Such focus comes from the observation of the developer's interests in the industrial application development using scenarios. Hsia et al. 11] suggested the procedures for scenario analysis, which use scenario trees and conceptual state machines to represent a n d analyze the scenarios. They study the techniques for scenario formalization, generation, and veri cation, but do not mention the issues of abstraction and integration of scenarios.. In Glinz's research 10], each scenario is transformed into statechart formalism, and is integrated into a global behavior. To i n tegrate each formally represented scenario, he suggests the composition rule for statechart templates which represent the relationship among the scenarios such as sequence, alternative, iteration, and concurrency. Abstraction of a speci c behavior or an actor is represented with a simpli ed statechart. This statechart is represented by only its name, omitting its internal behaviors. Thus, it cannot represent the interaction among its components and the state changes of the abstract component. Moreover, we believe that the notion of abstraction in Glinz's research i s n o t the representation of the high-level information elicited from user requirements, but only the omitted representation of statecharts to reduce the complexity of the drawn models. After the completion of all requirements with statecharts, each model can be abstracted(strictly speaking, can be simpli ed) with a simpli ed statechart.. Regnell suggested the UORE(Usage Oriented Requirement Engineering) method 23], which i s a n extension of use-case based analysis and design method. In this method, the use-case model is represented with message sequence charts. There are two considerations for abstraction in the UORE method. One is the abstraction of the interface part between users and systems. This postpones the design decision of the interface parts which consist of menu buttons, peripheral devices, and so on. The other is the abstraction for model itself. This simpli es the complex representation of models and improves the understandability and readability of the drawn models. However, these two cases do not support the real notion of abstraction. For the rst case, it is not the abstraction of system behaviors and states. The abstraction which is related to the hardware interface is one of the natural design techniques in common software development. The second case is the same as the abstract representation in Glinz's research.. The integrating method of scenarios represented with timed automata is suggested by Some et al. 27, 28] . This method de nes the interactions within a scenario in the rst step, and then, the stimuli and reactions for each interaction are identi ed. Scenario integration is processed by the evaluation of the conditions for the stimuli and their reactions. The inconsistency and incompleteness of the scenarios are detected by the evaluation of the conditions. The integrated scenario is represented by a global automata. This method does not consider the notion of abstraction because the condition of each i n teraction has speci c timing constraints. Desharnais et al. 9] i n tegrated state-based sequential scenarios. This method represents scenarios with a formal relation-based de nition and integrates the scenarios into a more global view of usersystem interaction. Scenarios are represented by means of relations, and their integration is de ned by means of relational operations. However, the restriction of this method is that the scenarios are sequential cases for only one user. Thus, concurrency of the system cannot be expressed in the scenario. In integrating sequential scenarios, the inconsistency and incompleteness problems are considered, but the problem on the di erent abstraction levels of each scenario remains in further works.. Other research includes the scenarios integration by nite state automata 17], the speci cation and composition of scenarios represented with high-level Petri net 16], the representation of interrelation of scenarios by message sequence charts 3], and so on 1, 4 , 1 9 ]. The researches mentioned above are interested in the scenario integration considering the inconsistency and incompleteness problems, but do not consider the notion of abstraction in scenario representation. Therefore, we propose a scenario modeling and analysis method, based on object-oriented Petri net, which provides the hierarchical representation of scenarios according to their abstraction levels, and also provides the incremental integration of scenarios satisfying the requirements of consistency and completeness.. 3 Hierarchical Object-Oriented Petri Net

O B I O O B B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O B B I O B O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B B I


Automated Pattern-Based Service Deployment in Programmable Networks This paper presents a flexible service deployment architecture for the automated, ondemand deployment of distributed services in programmable networks. The novelty of our approach is (a) the customization of the deployment protocol by utilizing modular building blocks, namely navigation patterns, aggregation patterns, and capability functions, and (b) the definition of a corresponding service descriptor. A customizable deployment protocol has several important advantages: It supports a multitude of services, and it allows for an ad hoc optimization of the protocol according to the specific needs of a service and the current network conditions. Moreover, our architecture provides an environment for studying new patterns which aim at reducing deployment latency and bandwidth for certain services. We demonstrate how the developed architecture can be used to setup a virtual private network, and we present measurements conducted with our prototype in the PlanetLab test network. Furthermore, a comparison of a distributed pattern with a centralized pattern illustrates the performance trade-off for different deployment strategies. In the last years, numerous distributed network services which can be deployed dynamically, such as firewalls, virtual private networks, video scaling, and load balancing have been proposed by the research community. Such services require the installation of service logic on multiple routers at specific locations within the network. For instance, a virtual private network requires the installation of an IPSec gateway on exactly one node within each of the VPN domains. Additionally, the node which is selected to run the IPSec gateway must provide resources such as bandwidth, CPU power, and memory space to operate the service. Current practice is to deploy distributed services manually. However, manual deployment is time consuming and error-prone. Moreover, since complexity increases with network size, manual deployment is not suited for large-scale networks. A better solution is to automate the service deployment process. The most challenging part in the service deployment process is the identification of nodes which provide the necessary resources to deploy a service. Several approaches target resource discovery in programmable networks. In [1] , the formal description of a hierarchical deployment mechanism based on the gather-compute-scatter algorithm is presented. This work concentrates on developing service deployment algorithms, but does not provide an implementation of a deployment protocol which applies the proposed algorithms. In [2] , a network control software is introduced which accepts demands from applications to discover available processing resources. With this approach, each node periodically broadcasts information about its available resources using the OSPF protocol.. In this paper, we present a service deployment architecture which applies on-demand resource discovery. That is, node resources are only queried when a service is about to be deployed within the network. We argue that in large networks which potentially support a broad range of services, continuous collection of node status data is inefficient. This is due to the fact that for a specific deployment operation (a) only a subset of all nodes needs to be queried, and (b) only a subset of all node status data is required. Moreover, collecting node status data on-demand guarantees that the collected data is always up-to-date. However, in order to keep service setup times short, on-demand resource discovery algorithms must be customized to the requirements of the service that is to be deployed. For instance, to deploy a VPN service only nodes within one of the domains to be connected by the VPN need to be queried. In contrast, for the deployment of a firewall nodes at the network border of the secured domain need to be queried.. Hence, we suggest a customizable service deployment protocol that is constructed from exchangeable protocol building blocks, namely patterns. The protocol is based on the concept of navigation patterns and aggregators introduced in [3] . We further modularize the protocol functionality by introducing a third building block, called capability function. Moreover, we define a corresponding service descriptor, and conduct measurements with a prototype of the service deployment architecture on the PlanetLab platform. This paper is organized as follows: Section 2 aims at familiarizing the reader with the concepts of pattern-based service deployment. In Section 3, we present a detailed description of our new approach to service deployment. The implemented service deployment prototype is presented in Section 4. Section 5 describes how our prototype can be applied to deploy a virtual private network. Section 6 presents an evaluation of our prototype based on measurements conducted in the PlanetLab [4] test environment. In Section 7, we draw our conclusions and give an outlook on future work. In this paper, we presented a flexible service deployment architecture for the automated, on-demand deployment of distributed services in programmable networks. The goal of our approach is to support the customization of the deployment protocol to specific service requirements. We achieved this goal by developing (i) a modular protocol architecture which is based on three classes of exchangeable deployment patterns, and (ii) a three-tier service description model which uses XML as service description language. Our implementation of the service deployment architecture includes six example deployment patterns, two of each pattern class. We have shown how the implemented patterns can be applied in a concrete deployment scenario, i.e., for setting up a virtual private network. Furthermore, we tested our pattern-based deployment protocol in the PlanetLab network. Tests have shown that a resource discovery operation over 83 PlanetLab nodes completes in around 40 s, while generating less than 500 kB of traffic within the network. Moreover, we demonstrated how the protocol performance can be optimized for a certain scenario by applying different deployment strategies. Our Bernhard Plattner is a Professor of Computer Engineering at ETH Zurich, where he leads the communication systems research group. His research currently focuses on applications of communication systems and higher layer protocols, and on new network architectures. Specifically, he has directed research on active networks, starting as early as 1996. He is also interested in new approaches for dynamic service creation and management, as well as practical aspects of information security.

O O B I O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O B I O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O B I O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O B I O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


Multi-view 3D Human Pose Estimation in Complex Environment We introduce a framework for unconstrained 3D human upper body pose estimation from multiple camera views in complex environment. Its main novelty lies in the integration of three components: single-frame pose recovery, temporal integration and model texture adaptation. Single-frame pose recovery consists of a hypothesis generation stage, in which candidate 3D poses are generated, based on probabilistic hierarchical shape matching in each camera view. In the subsequent hypothesis verification stage, the candidate 3D poses are re-projected into the other camera views and ranked according to a multi-view likelihood measure. Temporal integration consists of computing K-best trajectories combining a motion model and observations in a Viterbi-style maximum-likelihood approach. Poses that lie on the best trajectories are used to generate and adapt a texture model, which in turn enriches the shape likelihood measure used for pose recovery. The multiple trajectory hypotheses are used to generate pose predictions, augmenting the 3D pose candidates generated at the next time step.We demonstrate that our approach outperforms the stateof-the-art in experiments with large and challenging realworld data from an outdoor setting. The recovery of 3D human pose is an important problem in computer vision with many potential applications in human computer interfaces, motion analysis (e.g. sports, medical) and surveillance. 3D pose also provides informative, viewinvariant features for a subsequent activity recognition step. Despite the considerable advances that have been made over the past years (see next section), 3D human pose recovery remains essentially unsolved for unconstrained movement in dynamic and cluttered environment. The challenges involve estimating articulated motion of bodies of which the exact proportions are not known in advance, dealing with the underconstrained nature of the problem due to loss of depth information and/or (self) occlusion, and performing foreground-background segmentation. This paper presents a framework for the estimation of 3D human upper body movement from multiple views, which entails the combination of probabilistic single-frame 1 pose recovery, temporal integration and texture model adaptation. Using input from three calibrated cameras, we are able to handle arbitrary movement-i.e. not limited to walking and running-in cluttered scenes with non-stationary backgrounds (see Fig. 3 ). By integrating single-frame pose recovery within a tracking and prediction mechanism, there is no need to rely on specific initial poses to jump-start the pose estimation. The framework thus also entails automatic re-initialization after a period of failure.. Efficiency is an important design consideration. Singleframe pose recovery is implemented by a multi-stage cascade architecture, where candidate poses are increasingly pruned by the successive processing stages. Early processing stages are characterized by lighter computational costs per candidate pose, and a higher degree of inherent parallelism. For example, the pose hypothesis stage is performed by each camera independently. The computational burden is shifted as much as possible to an off-line stage, by matching a set of pre-rendered 2D pose (shape) exemplars, compactly organized in a pre-computed tree structure. Later processing stages are characterized by higher computational costs per remaining candidate pose and a stronger interaction across camera views. Take for example, the use of inverse kinematics for local pose optimization.. The current system also has some limitations. Like previous 3D pose recovery systems, it currently cannot handle a sizable amount of external occlusion. It furthermore assumes the existence of a 3D human model that roughly fits the person in the scene (we are able to use the same generic model for different male adults in the experiments). Lastly, the system expects subjects to be roughly in a standing position for pose initialization, for computational cost reasons. We presented a framework for unconstrained 3D human upper body pose estimation from multiple camera views in a complex environment. The main novelty lies in the integration of three components: single-frame pose recovery, temporal integration and model texture adaptation. The second contribution concerns the way single-frame pose recovery is performed: hypotheses are generated in each camera independently based on probabilistic hierarchical shape matching, and information is fused at the pose parameter level in an efficient, multi-stage process.. We demonstrated an improvement versus the state-ofthe-art in a dozen of challenging real-world sequences depicting different actors performing unscripted movements. Further work will be necessary to deal with multiple people under occlusion.. • N * ≈ 20000 Maximum number of 2D pose exemplars that can still be practically handled with a partitional clustering algorithm of quadratic complexity, on a particular hardware (Sect. • γ l Image grid size (in pixel) for interest locations for matching at tree level l. γ 1 = 6 px, γ 2 = 3 px, γ 3 = 1 px, γ 4 = 1 px (Sect. 3.4.3).. • τ l Threshold on posterior for nodes at tree level l. τ 1 = 0.01, τ 2 = 0.016, τ 3 = 0.02, τ 4 = 0.024 (Sect. 3.4.3).. • u x Area of non-maximum suppression at process stage x, before truncation. In particular, u P osHyp = 2 pixels (Sect. 3.4.3), u P osSel = 1.25 cm (Sect. 3.5), u P osV erEx = 1.75 cm (Sect. 3.6.1) u P osV erRdr = 0 cm (no non-maximum suppression) (Sect. 3.6.2). • K x : Number of hypotheses that are generated by process stage x, after truncation. In particular, K P osHyp ≈ 300000 value is determined by τ 1 · · · τ 4 (Sect. 3.4.3), K P osSel = 30000 (Sect. 3.5), K P osV erEx = 2000 (Sect. 3.6.1), K P osV erRdr = 800 (Sect. 3.6.2), and K P osV erRdrOpt = 50 (Sect. 3.6.3). A.5 Temporal Integration (Sect. 3.7). • T = 50 Number of image frames of time interval for which the best trajectories are computed • K traj = 500 Number of best trajectories obtained by ListViterbi algorithm A.6 Texture-Based Model Adaptation (Sect. 3.8). • α = 0.1 Learning rate pixel-based texture adaptation. • R b Texture model resolution (in pixels) for different body parts. R torso = 32 px × 32 px, R head = R u.arm = R l.arm = 16 px × 16 px, R neck = R hand = 8 px × 8 px The experiments demonstrated a new quality to 3D pose estimation for arbitrary (single) human movement in a noisy and uncontrolled environment. The remaining failure mode of the system concerns prolonged "ambiguous" poses with the hands close to the torso; the silhouette-based approach stands little chance in recovering exact hand position, furthermore, most clothing does not contain appreciable texture differences between torso and arms. Further work could add the segmentation-of and matching-with the weak internal edges to the later process stages. We implemented the system in unoptimized C++ code; it currently requires about 30-40 s per frame (i.e. total over three cameras at a timestamp) to recover 3D pose on a 3 GHz Intel PC. This is not fast in absolute terms, but it seems to compare favorably with previously reported processing speeds in literature concerning 3D pose recovery with generative models against non-stationary background (e.g. Balan and Black 2006; Gall et al. 2010; Kohli et al. 2008; Lee and Cohen 2006; Lee and Nevatia 2009 ), yet direct comparisons are difficult due to the differing types of movement considered (for example, unconstrained upper body movement vs. whole-body walking). Computing time approximately breaks down onto the separate processing stages as given in Table 4 . The main processing bottlenecks are the 2D pose exemplar matching (Sect. 3.4.3), the pose verification by graphical rendering (Sect. 3.6.2) and local pose optimization (Sect. 3.6.3) stages. These stages could be parallelized, allowing for a near-linear reduction of processing time with available CPU/GPU cores. However, we did not exploit parallelism in our implementation, neither at the camera-, nor at the pose solution-or vertex-level. The only exception to this was local pose estimation, where the pose solutions were distributed over the available four processor cores.. Another way to improve system efficiency is by parameter setting. We did not spend major time on parameter tuning and selected conservative truncation thresholds (e.g. τ 1 , . . . , τ L , K P osSel , K P osV erEx , K P osV erRdr ) for the various processing stages. Gavrila and Munder (2007) describe an automatic procedure to optimize parameters in a multistage cascade architecture, based on successive ROC optimization. All in all, significant optimization potential remains. Future work involves the recovery of whole-body pose and that of multiple, potentially occluding, people. An extension of the chosen exemplar-based approach to wholebody recovery (or to multiple body models for capturing a larger variety of people) is straightforward. It will however, at least for the near future, require coarser joint angle discretizations, in order to keep the additional memory requirements in check. Its effect on pose recovery accuracy remains to be investigated. We do expect a future adaptation of a generic 3D human shape model (see work by Balan et al. 2007; Gall et al. 2009 ) to the particular person in the scene to result in more accurate likelihood estimation, alleviating some of the above-mentioned pose discretization effect.. Multi-person pose recovery could be achieved by executing the system multiple times on all recognized 3D blobs in the image pre-processing stage (see Sect. 3.3). The system could be built on top of a more sophisticated (multi-) 3D blob tracking approach, e.g. Fleuret et al. (2008) , Liem and Gavrila (2009) , to better handle track consistency in case of multiple persons being in close vicinity, i.e. avoidance of ID changes. There is meanwhile an extensive literature on 3D human pose estimation. We refer to a selection of papers here which we consider most relevant to this paper. For a more exhaustive listing, see surveys by Forsyth et al. (2005) , Gavrila (1999) , Moeslund et al. (2006) , .. One line of research has focused on 3D model-based tracking; i.e. given a reasonably accurate 3D human model and an initial 3D pose, predict the pose at the next time step using a particular dynamical and observation model (Balan and Black 2006; Brubaker et al. 2010; Deutscher and Reid 2005; Drummond and Cipolla 2001; Fossati et al. 2009; Gavrila and Davis 1996; Hasler et al. 2009; Kakadiaris and Metaxas 2000; Lee and Elgammal 2010; Li et al. 2010; Ong et al. 2006; Peursum et al. 2010; Roberts et al. 2006; Rosenhahn and Brox 2007; Stenger et al. 2006; Vondrak et al. 2008; Xu and Li 2007) . Multi-hypothesis approaches based on particle filtering (Brubaker et al. 2010; Deutscher and Reid 2005; Ong et al. 2006; Peursum et al. 2010; Xu and Li 2007) or non-parametric belief propagation (Sigal et al. 2004 ) are used for increased robustness. However, the high dimensionality of the pose parameter space necessitates researchers to employ strong motion priors (i.e. known action classes such as walking, running) and/or various sequential sampling techniques. In practice, tracking soon goes astray if no recovery mechanism is added.. Another line of research has dealt with 3D pose initialization. Work in this category can be distinguished by the number of cameras used. Multi-camera systems for 3D pose initialization were so far applied in controlled indoor environments. The near-perfect foreground segmentation resulting from the stationary background, together with the many cameras used (> 5), allows to recover pose by Shapefrom-Silhouette techniques (Cheung et al. 2005a (Cheung et al. , 2005b Corazza et al. 2010; Kehl and Gool 2006; Mikic et al. 2003; Starck and Hilton 2003; Sundaresan and Chellappa 2009) . A new line of research goes beyond the recovery of pose parameters to the estimation of the non-rigid surface of the 3D human model (Balan et al. 2007; Gall et al. 2009 ).. Single camera systems for 3D pose initialization can be sub-divided whether they use generative or learning-based approaches. Learning-based approaches construct a mapping between 3D pose and 2D image observables using machine learning techniques (Agarwal and Triggs 2006; Bo and Sminchisescu 2010; Bissacco et al. 2007; Kanaujia et al. 2007; Rogez et al. 2008; Shakhnarovich et al. 2003) . These approaches are conceptually appealing and fast, but questions still remain regarding their scalability to arbitrary poses. Certainly, a large number of examples would be needed in that case to allow for successful regression, given the ill conditioning and high dimensionality of the problem (most experimental results involve restricted movements, i.e. walking). Furthermore, learning-based approaches tend to rely on good foreground segmentation.. On the other hand, pose initialization using 3D generative models (Kohli et al. 2008 ; Lee and Cohen 2006) involves finding the best match between model projections and image, and retrieving the associated 3D pose. 3D generative models typically involve compositions of volumetric primitives like ellipsoids or cones (Forsyth et al. 2005; Gavrila 1999 ; Moeslund et al. 2006) . Alternatives involve linear subspace models, derived from a training set of 3D human body scans (SCAPE, Balan et al. 2007 ) and mesh models (e.g. Hasler et al. 2009 ).. Pose initialization using 2D generative models involves 2D pose recovery (Andriluka et al. 2009; Ferrari et al. 2009; Mori and Malik 2006; Ramanan et al. 2007 ) followed by a 3D inference step (Lee and Nevatia 2009 ) with respect to the joint locations. In order to reduce the combinatorial complexity associated with pose recovery, previous generative approaches apply part-based techniques (Sigal et al. 2004; Bergtholdt et al. 2010) . As far as these involve search space decomposition (i.e. searching first for the torso, then arms and legs) (Mori and Malik 2006; Navaratnam et al. 2005; Ramanan et al. 2007) , they are error prone; estimation mistakes made early on based on partial model knowledge cannot be corrected later on. In practice, this means that instances with an appreciable amount of torso movement and rotation are difficult to handle. It proves difficult to combine an efficient inferencing mechanism on body parts with the enforcement of multi-part constraints (e.g. dynamics, appearance); suggest that part-based approaches are probably best to provide an efficient proposal function for estimation with a more centralized representation of the body (e.g. a kinematic tree).. Methods for pose initialization can serve to initialize the above-mentioned trackers. An increasingly popular alternative is their use in "tracking-as-recognition" approaches, especially when no strong motion priors are available. Here, pose estimates obtained independently at each time instant are integrated to consistent trajectories, taking into account a more generic motion model. This is typically achieved by Markov chain optimization (Fossati et al. 2007; Lee and Nevatia 2009; Lv and Nevatia 2007; Navaratnam et al. 2005; Peursum et al. 2007) .. Given the extensive amount of work done on human 3D pose estimation, it has been difficult to assess how the various approaches stack against each other. In an upcoming special issue of this journal, make an important contribution in this regard, by providing the "HumanEva" data set. It contains a sizeable amount of multivideo and synchronized motion capture data of humans performing a set of predefined actions in a controlled indoor environment. Together with the provided motion capture ground truth and baseline algorithm, it allows other researchers to benchmark their 3D pose estimation systems on a common data set (Bergtholdt et al. 2010; Bo and Sminchisescu 2010; Brubaker et al. 2010; Corazza et al. 2010; Gall et al. 2010; Peursum et al. 2010; Lee and Elgammal 2010; Li et al. 2010) . Our experimental data consists of recordings from three synchronized color CCD cameras looking over a train station platform. In 12 sequences (about 10 s on average, captured at 20 Hz), various actors perform unscripted movements, such as walking, gesticulation and waving. The setting is challenging; the movements performed contain a sizable amount of torso turning, the background is cluttered and non-stationary (people are walking in the background, trains are passing by), furthermore, there are appreciable lighting changes. The realism of the dataset in the context of surveillance was the key motivation for using it as our primary dataset for evaluation. The evaluation methodology we use is similar to , both in terms of the 3D pose error metric (7) and the baseline algorithm (Deutscher and Reid 2005) . Our data is made public to facilitate benchmarking. 2 Cameras were calibrated using (Bouguet 2003) ; this enabled the recovery of the ground plane. Ground truth pose was manually labeled for all frames of the data set. Considering the quality of calibration and labeling, we estimate the ground truth accuracy to be within 4 cm. We used a single generic human model to capture the three male adults in the scene (one male wore two different outfits). To obtain an indication of the shape variations involved, we handfitted personalized human-outfit models and found the average vertex distance between the used generic and the tuned reference models to be 3.2 cm, 2.6 cm, 2.9 cm and 3.7 cm, respectively, in a canonical pose (i.e. arms stretched laterally, at 90 • elevation).. All distributions described in Sects. 3.4.3, 3.5 and 3.6 were learned by a leave-one-out approach for each test sequence. The generic motion model (Sect. 3.7) was derived from the aggregated CMU MoCap data 3 ; after some conver- sions to the degrees of freedom of our shape model and our frame rate, the latter yielded 756,844 frames for training.

O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O 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Fuzzy Description Logic Programs under the Answer Set Semantics for the Semantic Web Vagueness and imprecision abound in multimedia information processing and retrieval. In this paper, towards dealing with vagueness and imprecision in the reasoning layers of the Semantic Web, we present an approach to fuzzy description logic programs under the answer set semantics. We generalize normal description logic programs (dl-programs) under the answer set semantics by fuzzy vagueness and imprecision. We define a canonical semantics of positive and stratified fuzzy dl-programs in terms of a unique least model and iterative least models, respectively. We then define the answer set semantics of general fuzzy dlprograms, and show in particular that all answer sets of a fuzzy dl-program are minimal models, and that the answer set semantics of positive and stratified fuzzy dl-programs coincides with their canonical least model and iterative least model semantics, respectively. Furthermore, we also provide a characterization of the canonical semantics of positive and stratified fuzzy dl-programs in terms of a fixpoint and an iterative fixpoint semantics, respectively. The Semantic Web [1, 7] aims at an extension of the current World Wide Web by standards and technologies that help machines to understand the information on the Web so that they can support richer discovery, data integration, navigation, and automation of tasks. The main ideas behind it are to add a machine-readable meaning to Web pages, to use ontologies for a precise definition of shared terms in Web resources, to use KR technology for automated reasoning from Web resources, and to apply cooperative agent technology for processing the information of the Web. * Alternate address: Institut für Informationssysteme, TU Wien, Favoritenstr. 9-11, A-1040 Wien, Austria; lukasiewicz@kr.tuwien.ac.at.. The Semantic Web consists of several hierarchical layers, where the Ontology layer, in form of the OWL Web Ontology Language [34, 11] (recommended by the W3C), is currently the highest layer of sufficient maturity. OWL consists of three increasingly expressive sublanguages, namely OWL Lite, OWL DL, and OWL Full. OWL Lite and OWL DL are essentially very expressive description logics with an RDF syntax [11] . As shown in [9] , ontology entailment in OWL Lite (resp., OWL DL) reduces to knowledge base (un)satisfiability in the description logic SHIF(D) (resp., SHOIN (D)). On top of the Ontology layer, the Rules, Logic, and Proof layers of the Semantic Web will be developed next, which should offer sophisticated representation and reasoning capabilities. As a first effort in this direction, RuleML (Rule Markup Language) [2] is an XMLbased markup language for rules and rule-based systems, whereas the OWL Rules Language [10] is a first proposal for extending OWL by Horn clause rules.. A key requirement of the layered architecture of the Semantic Web is to integrate the Rules and the Ontology layer. In particular, it is crucial to allow for building rules on top of ontologies, that is, for rule-based systems that use vocabulary from ontology knowledge bases. Another type of combination is to build ontologies on top of rules, which means that ontological definitions are supplemented by rules or imported from rules. Towards this goal, the works [5, 6] have proposed description logic programs (or simply dlprograms), which are of the form KB = (L, P ), where L is a knowledge base in a description logic and P is a finite set of description logic rules (or simply dl-rules). Such dlrules are similar to usual rules in logic programs with negation as failure, but may also contain queries to L in their bodies, which are given by special atoms (on which possibly default negation may apply). Another important feature of dl-rules is that queries to L also allow for specifying an input from P , and thus for a flow of information from P to L, besides the flow of information from L to P , given by any query to L. Hence, description logic programs allow for building rules on top of ontologies, but also (to some extent) building ontologies on top of rules. In this way, additional knowledge (gained in the program) can be supplied to L before querying. The semantics of dl-programs was defined in [5] and [6] as an extension of the answer set semantics by Gelfond and Lifschitz [8] and the well-founded semantics by Van Gelder, Ross, and Schlipf [33] , respectively, which are the two most widely used semantics for normal logic programs. The description logic knowledge bases in dl-programs are specified in the description logics SHIF(D) and SHOIN (D).. In [17, 18] , towards sophisticated representation and reasoning techniques that also allow for modeling probabilistic uncertainty in the Rules, Logic, and Proof layers of the Semantic Web, we have presented probabilistic description logic programs (or simply probabilistic dl-programs), which generalize dl-programs under the answer set and the well-founded semantics by probabilistic uncertainty. They have been developed as a combination of dl-programs with Poole's independent choice logic (ICL) [23] .. In this paper, we continue this line of research towards more sophisticated representation and reasoning techniques for the Semantic Web. We present fuzzy description logic programs (or simply fuzzy dl-programs) under the answer set semantics, which are a combination of fuzzy description logics with fuzzy normal programs under the answer set semantics. They generalize dl-programs under the answer set semantics by fuzzy vagueness and imprecision in both the description logic and the logic program component. Even though there has been previous work on positive fuzzy description logic programs by Straccia [30, 31] , to our knowledge, this is the first approach to fuzzy description logic programs with default negation in rule bodies. Furthermore, differently from Straccia, we also allow for a flow of information from the logic program component to the description logic component of a fuzzy dl-program.. The main contributions of this paper are as follows:. • We introduce a simple fuzzy extension of SHIF(D) resp. SHOIN (D), which allows for fuzzy atomic concept and fuzzy role assertions, and which is based on a mapping to several layers of ordinary atomic concepts and roles in SHIF(D) resp. SHOIN (D).. • We introduce fuzzy dl-programs, which properly generalize dl-programs in [5] (where rule bodies may contain default-negated atoms) by fuzzy vagueness and imprecision. We define a natural semantics of positive and stratified fuzzy dl-programs in terms of a unique least model and iterative least models, respectively.. • We then define the answer set semantics of general fuzzy dl-programs. We also show that all answer sets of a fuzzy dl-program are minimal models, and that the answer set semantics of positive and stratified fuzzy dl-programs coincides with their canonical least model and iterative least model semantics, respectively.. • We also provide a characterization of the canonical semantics of positive and stratified fuzzy dl-programs in terms of a fixpoint and an iterative fixpoint semantics.. The rest of this paper is organized as follows. In Section 2, we recall the description logics SHIF(D) and SHOIN (D). In Section 3, we define our simple fuzzy extension of SHIF(D) resp. SHOIN (D). Section 4 introduces fuzzy dl-programs, and defines the canonical semantics of positive and stratified fuzzy dl-programs, as well as the answer set semantics of general fuzzy dl-programs. In Section 5, we characterize the canonical models of positive and stratified fuzzy dl-programs in terms of a fixpoint and an iterative fixpoint semantics. Section 6 summarizes our main results and gives an outlook on future research.

B I I I O O B I I O O B I B I I O O O O O O O O O O O O O B I I O O O O O O B I O O O O O B I I I O O B I I O O O O O O O O O B I I O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O B I I I O O O O O O B I I O O O O O B I I O B I I O O B I I O O O O O B I I O O B I I O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O


An architectural style for high-performance asymmetrical parallel computations Researchers with deep knowledge of scientific domains are now developing highly-adaptive and irregular (asymmetrical ) parallel computations, leading to challenges in both delivery of data for computation and mapping of processes to physical resources. Using software engineering principles, we have developed a new communications protocol and architectural style for asymmetrical parallel computations called ADaPT.Utilizing the support of architecturally-aware middleware, we show that ADaPT provides a more efficient solution in terms of message passing and load balancing than asymmetrical parallel computations using collective calls in the Message-Passing Interface (MPI) or more advanced frameworks implementing explicit load-balancing policies. Additionally, developers using ADaPT gain significant windfall from good practices in software engineering, including implementation-level support of architectural artifacts and separation of computational loci from communication protocols. In recent years, as the cost-to-performance ratio of consumer hardware has continued to decrease, computational clusters consisting of fast networks and commodity hardware have become a common sight in research laboratories. growing number of physicists, biologists, chemists, and computer scientists have developed highly-adaptive and irregular parallel applications that are characterized by computational intensity, loosely-synchronous parallelism and dynamic computation. Because the computation time of each parallel process varies significantly for this class of computation, we shall refer to them as asymmetrical parallel computations. Adaptive mesh refinements for the simulation of crack growth, combinatorial search applications used in artificial intelligence, and partial differential equation field solvers [2] are examples of asymmetrical computations.. While supercomputing platforms available to us continue to increase performance, our ability to build software capable of matching theoretical limits is lacking [8] . At the same time, researchers with significant depth of knowledge in a scientific domain but with limited software experience are confounded by the interface bloat of libraries such the Message-Passing Interface (MPI), which has 12 different routines for point-to-point communications alone [5] .. Would-be practitioners of high-performance computing are introduced early to the mantra of optimization. The myth that high-level concepts inherent to software engineering principles, such as "separation of concerns," result in inefficiencies at the performance level has caused these researchers to eschew best practices of traditional software development in favor of highly-optimized library routines.. We contend that a sound software engineering solution to asymmetrical parallel computations provides decoupling of connectors from computational loci and reduces the complexity of development for the programmer while still providing an efficient solution both in terms of load-balancing and message-delivery. In this paper, we present such a solution.. In the next section, we will discuss our motivations for creating the ADaPT protocol and architecture, including the load-balancing inefficiencies of "optimized" communications libraries when computing asymmetrical parallel computations. We will then present ADaPT, a communications protocol and associated software architecture for asymmetrical computations. Additionally, we will present analysis which shows ADaPT's ability to outperform both MPI and other load-balancing frameworks using traditional work-sharing strategies. We conclude with an overview of future research opportunities afforded by ADaPT. While ADaPT is clearly an applicable architectural style to high-performance computing, we make no claim as to its monopoly of the field. In future work, we hope to build a more substantial architectural framework for high-performance computing which provides more underlying protocol choices and further assists developers in code migration to new platforms including SMP and other shared-memory machines. We hope to demonstrate the ease of system design and implementation via architectures to the high-performance community without serious performance degradation, as is currently the prevalent though.. Further enhancements to the ADaPT protocol and architecture will include refinement of its topological constraints to encapsulate both data-parallel stages of computation and higher-level workflow stages using multiple layers of masters and workers connected between more advanced ADaPT connectors (themselves perhaps distributed across multiple physical nodes). Also, we hope to further investigate the tradeoffs associated with alternate unsubscription policies and the effects of "pumping" the parallel computation by modifying delivery rates to be faster than average computation rates.. This work was supported by the NSF 0312780 grant. Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the National Science Foundation. The authors also wish to thank the anonymous reviewers for their helpful comments. This work has been motivated by our experience with two key classes of existing approaches: use of optimized communications libraries such as MPI [4] , and messagepassing frameworks which implement load-balancing strategies based on work sharing.

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A projective invariant generalization of the de Casteljau algorithm A projective invariant generalization of the de Casteljau algorithm is described by using the cross ratio and an auxiliary line. We describe the implicit form of the section conics obtained by the algorithm proposed in this paper. Finally, we show how to construct specific conic sections using this approach.

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