Query: Pose tracking from natural features on mobile phones

Relevant passages:
Parallel Tracking and Mapping for Small AR Workspaces <=SEP=> This paper presents a method of estimating camera pose in an unknown scene. While this has previously been attempted by adapting SLAM algorithms developed for robotic exploration, we propose a system specifically designed to track a hand-held camera in a small AR workspace. We propose to split tracking and mapping into two separate tasks, processed in parallel threads on a dual-core computer: one thread deals with the task of robustly tracking erratic hand-held motion, while the other produces a 3D map of point features from previously observed video frames. This allows the use of computationally expensive batch optimisation techniques not usually associated with real-time operation: The result is a system that produces detailed maps with thousands of landmarks which can be tracked at frame-rate, with an accuracy and robustness rivalling that of state-of-the-art model-based systems.

Fast Keypoint Recognition in Ten Lines of Code <=SEP=> While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle perspective distortion. In this paper, we show that formulating the problem in a Naive Bayesian classification framework makes such preprocessing unnecessary and produces an algorithm that is simple, efficient, and robust. Furthermore, it scales well to handle large number of classes. To recognize the patches surrounding keypoints, our classifier uses hundreds of simple binary features and models class posterior probabilities. We make the problem computationally tractable by assuming independence between arbitrary sets of features. Even though this is not strictly true, we demonstrate that our classifier nevertheless performs remarkably well on image datasets containing very significant perspective changes.

Face to Face Collaborative AR on Mobile Phones <=SEP=> Mobile phones are an ideal platform for augmented reality. In this paper we describe how they can also be used to support face to face collaborative AR gaming. We have created a custom port of the ARToolKit library to the Symbian mobile phone operating system and then developed a sample collaborative AR game based on this. We describe the game in detail and user feedback from people who have played the game. We also provide general design guidelines that could be useful for others who are developing mobile phone collaborative AR applications.

USING CAMERA-EQUIPPED MOBILE PHONES FOR INTERACTING WITH REAL-WORLD OBJECTS <=SEP=> The idea described in this paper is to use the built-in cameras of consumer mobile phones as sensors for 2-dimensional visual codes. Such codes can be attached to physical objects in order to retrieve object-related information and functionality. They are also suitable for display on electronic screens. The proposed visual code system allows the simultaneous detection of multiple codes, introduces a position-independent coordinate system, and provides the phone’s orientation as a parameter. The ability to detect objects in the user’s vicinity offers a natural way of interaction and strengthens the role of mobile phones in a large number of application scenarios. We describe the hardware requirements, the design of a suitable visual code, a lightweight recognition algorithm, and present some example applications.

Robust Visual Tracking for Non-Instrumented Augmented Reality <=SEP=> This paper presents a robust and flexible framework for augmented reality which does not require instrumenting either the environment or the workpiece. A model-based visual tracking system is combined with with rate gyroscopes to produce a system which can track the rapid camera rotations generated by a head-mounted camera, even if images are substantially degraded by motion blur. This tracking yields estimates of head position at video field rate (50Hz) which are used to align computer-generated graphics on an optical see-through display. Nonlinear optimisation is used for the calibration of display parameters which include a model of optical distortion. Rendered visuals are pre-distorted to correct the optical distortion of the display.

Engagement in Multimedia Training Systems <=SEP=> Two studies examined user engagement in two type multimedia training systems -a more passive medium, videotape, and a less passive medium, interactive softw Each study compared engagement in three formats: the Text format contained text and still images, the Audio format contained audio and still images, and the Video format contained audio and video images. In both studies, engagement was lower in the Text condition than in the Video condition. However, there were no differences in engagement between Text and Audio in the videotapebased training, and no differences between Audio and Video in the computer-based training.

Action recognition based on a bag of 3D points <=SEP=> This paper presents a method to recognize human actions from sequences of depth maps. Specifically, we employ an action graph to model explicitly the dynamics of the actions and a bag of 3D points to characterize a set of salient postures that correspond to the nodes in the action graph. In addition, we propose a simple, but effective projection based sampling scheme to sample the bag of 3D points from the depth maps. Experimental results have shown that over 90% recognition accuracy were achieved by sampling only about 1% 3D points from the depth maps. Compared to the 2D silhouette based recognition, the recognition errors were halved. In addition, we demonstrate the potential of the bag of points posture model to deal with occlusions through simulation.

Birdbrains could teach basal ganglia research a new song <=SEP=> Recent advances in anatomical, physiological and histochemical characterization of avian basal ganglia neurons and circuitry have revealed remarkable similarities to mammalian basal ganglia. A modern revision of the avian anatomical nomenclature has now provided a common language for studying the function of the cortical-basal-ganglia-cortical loop, enabling neuroscientists to take advantage of the specialization of basal ganglia areas in various avian species. For instance, songbirds, which learn their vocal motor behavior using sensory feedback, have specialized a portion of their cortical-basal ganglia circuitry for song learning and production. This discrete circuit dedicated to a specific sensorimotor task could be especially tractable for elucidating the interwoven sensory, motor and reward signals carried by basal ganglia, and the function of these signals in task learning and execution.

Robotic Arm Based 3D Reconstruction Test Automation <=SEP=> The 3-D reconstruction involves the construction of a 3-D model from a set of images. The 3-D reconstruction has varied uses that include 3-D printing, the generation of 3-D models that can be shared through social media, and more. The 3-D reconstruction involves complex computations in mobile phones that must determine the pose estimation. The pose estimation involves the process of transforming a 2-D object into 3-D space. Once the pose estimation is done, then the mesh generation is performed using the graphics processing unit. This helps render the 3-D object. The competitive advantages of using hardware processors are to accelerate the intensive computation using graphics processors and digital signal processors. The stated problem that this technical paper addresses is the need for a reliable automated test for the 3-D reconstruction feature. The solution to this problem involved the design and development of an automated test system using a programmable robotic arm and rotor for precisely testing the quality of 3-D reconstruction features. The 3-D reconstruction testing involves using a robotic arm lab to accurately test the algorithmic integrity and end-to-end validation of the generated 3-D models. The robotic arm can move the hardware at different panning speeds, specific angles, fixed distances from the object, and more. The ability to reproduce the scanning at a fixed distance and the same panning speed helps to generate test results that can be benchmarked by different software builds. The 3-D reconstruction also requires a depth sensor to be mounted onto the device under examination. We use this robotic arm lab for functional, high performance, and stable validation of the 3-D reconstruction feature. This paper addresses the computer vision use case testing for 3-D reconstruction features and how we have used the robotic arm lab for automating these use cases.

A Ka-Band CMOS Wilkinson Power Divider Using Synthetic Quasi-TEM Transmission Lines <=SEP=> This work presents a Ka-band two-way 3 dB Wilkinson power divider using synthetic quasi-transverse electromagnetic (TEM) transmission lines (TLs). The synthetic quasi-TEM TL, also called complementary-conducting-strip TL (CCS TL), is theoretically analyzed. The equivalent TL model, whose production is based on the extracted results, is applied to the power divider design. The prototype is fabricated by the standard 0.18 mum 1P6M CMOS technology, showing the circuit size of 210.0 mumtimes390.0 mum without contact pads. The measurement results, which match the 50 Omega system, reveal perfect agreements with those of the simulations. The comparison reveals the following characteristics. The divider exhibits an equal power-split with the insertion losses (S21 and S31) of 3.65 dB. The return losses (S11, S22 and S33) of the prototype are higher than 10.0 dB from 30.0 to 40.0 GHz.

Using Patterns to Capture Architectural Decisions <=SEP=> Throughout the software design process, developers must make decisions and reify them in code. The decisions made during software architecting are particularly significant in that they have system-wide implications, especially on the quality attributes. However, architects often fail to adequately document their decisions because they don't appreciate the benefits, don't know how to document decisions, or don't recognize that they're making decisions. This lack of thorough documentation. This paper provides information about a decision's rationale and consequences, architecture patterns can help architects better understand and more easily record their decisions.

A model for concentric tube continuum robots under applied wrenches <=SEP=> Continuum robots made from telescoping precurved elastic tubes enable base-mounted actuators to specify the curved shapes of robots as thin as standard surgical needles. While free space beam mechanics-based models of the shape of these ‘active cannulas’ exist, current models cannot account for external forces and torques applied to the cannula by the environment. In this paper we apply geometrically exact beam theory to solve the statics problem for concentric-tube continuum robots. This yields the equivalent of forward kinematics for an active cannula with general tube precurvature functions and arbitrarily many tubes, under loading from a general wrench distribution. The model achieves average experimental tip errors of less than 3 mm over the workspace of a prototype active cannula subject to various tip forces.

The feasible workspace analysis of a set point control for a cable-suspended robot with input constraints and disturbances <=SEP=> This paper deals with the characterization of reachable domain of a set-point controller for a cable-suspended robot under disturbances and input constraints. The main contribution of the paper is to calculate the feasible domain analytically through the choice of a control law, starting from a given initial condition. This analytical computation is then recursively used to find a second feasible domain starting from a boundary point of the first feasible domain. Hence, this procedure allows to expand the region of feasible reference signals by connecting adjacent domains through common points. Finally, the effectiveness of the proposed method is illustrated by numerical simulations on a kinematically determined cable robot with six cables.

Graph Embedding Problem Settings Graph Embedding Input Graph Embedding Output Homogeneous Graph Heterogeneous Graph Graph with Auxiliary Information Graph Constructed from Non-relational Data Node Embedding Edge Embedding Hybrid Embedding Whole-Graph Embedding Graph Embedding Techniques Matrix Facto <=SEP=> Graph is an important data representation which appears in a wide diversity of real-world scenarios. Effective graph analytics provides users a deeper understanding of what is behind the data, and thus can benefit a lot of useful applications such as node classification, node recommendation, link prediction, etc. However, most graph analytics methods suffer the high computation and space cost. Graph embedding is an effective yet efficient way to solve the graph analytics problem. It converts the graph data into a low dimensional space in which the graph structural information and graph properties are maximumly preserved. In this survey, we conduct a comprehensive review of the literature in graph embedding. We first introduce the formal definition of graph embedding as well as the related concepts. After that, we propose two taxonomies of graph embedding which correspond to what challenges exist in different graph embedding problem settings and how the existing work address these challenges in their solutions. Finally, we summarize the applications that graph embedding enables and suggest four promising future research directions in terms of computation efficiency, problem settings, techniques and application scenarios.

Local sensor system for badminton smash analysis <=SEP=> This paper presents a development of a sensory system for analysis of badminton smashes. During a badminton game, the ability to execute a powerful smash is fundamental for a player to be competitive. In most games, the winning factor for the game is often attributed to a high shuttle speed during the execution of a smash. It was envisioned that the shuttle speed can be correlated from the speed of the rackets head. To help analyze the key relationship between the racket speed and the shuttle ball speed, a series of sensors were integrated into a conventional racket. The aim of this investigation is to develop a sensor system that will facilitate the quantifiable analysis of the badminton smash. It was determined in a previous investigation that a single accelerometer is insufficient to determine the two or three dimensional trajectory of the racket. Therefore a low mass compact, 2-axes piezoelectric accelerometers was applied to the head of the racket. An acoustic shock sensor was also mounted on the racket head to identify the instant of the contact event. It was hypothesized that the magnitude of the acoustic signal, associated with the hitting event, and the final speed of the racket when fused could provide a good correlation with the shuttle speed. The fuzzy inference system and ANFIS (Adaptive Neuro-Fuzzy Inferior System) sensor fusion techniques was investigated. It has been demonstrated that it is possible to analyze the performance of the smashing stroke based on the system developed in this investigation which in turn may, with further develop by a useful aid to badminton coaches and the methods developed may also be applicable to other applications.

Vital, Sophia, and Co. - The Quest for the Legal Personhood of Robots <=SEP=> The paper examines today’s debate on the legal status of AI robots, and how often scholars and policy makers confuse the legal agenthood of these artificial agents with the status of legal personhood. By taking into account current trends in the field, the paper suggests a twofold stance. First, policy makers shall seriously mull over the possibility of establishing novel forms of accountability and liability for the activities of AI robots in contracts and business law, e.g., new forms of legal agenthood in cases of complex distributed responsibility. Second, any hypothesis of granting AI robots full legal personhood has to be discarded in the foreseeable future. However, how should we deal with Sophia, which became the first AI application to receive citizenship of any country, namely, Saudi Arabia, in October 2017? Admittedly, granting someone, or something, legal personhood is—as always has been—a highly sensitive political issue that does not simply hinge on rational choices and empirical evidence. Discretion, arbitrariness, and even bizarre decisions play a role in this context. However, the normative reasons why legal systems grant human and artificial entities, such as corporations, their status, help us taking sides in today’s quest for the legal personhood of AI robots. Is citizen Sophia really conscious, or capable of suffering the slings and arrows of outrageous scholars?

Working memory as an emergent property of the mind and brain <=SEP=> Cognitive neuroscience research on working memory has been largely motivated by a standard model that arose from the melding of psychological theory with neuroscience data. Among the tenets of this standard model are that working memory functions arise from the operation of specialized systems that act as buffers for the storage and manipulation of information, and that frontal cortex (particularly prefrontal cortex) is a critical neural substrate for these specialized systems. However, the standard model has been a victim of its own success, and can no longer accommodate many of the empirical findings of studies that it has motivated. An alternative is proposed: Working memory functions arise through the coordinated recruitment, via attention, of brain systems that have evolved to accomplish sensory-, representation-, and action-related functions. Evidence from behavioral, neuropsychological, electrophysiological, and neuroimaging studies, from monkeys and humans, is considered, as is the question of how to interpret delay-period activity in the prefrontal cortex.

Innovating with Concept Mapping <=SEP=> Student-generated concept maps (Cmaps) have been the preferred choice to design assessment tasks, which are time-consuming in real classroom settings. We have proposed the use of Cmap with errors (elaborated by teachers) to develop assessment tasks, as a way to address the logistical practicality obstacles usually found in classrooms. This paper compared two different tasks, finding the errors and judging the selected propositions in Cmap with errors, exploring two topics with different levels of difficulty. Our results confirmed Cmap with errors as a straightforward approach to include concept mapping into the classroom routine to foster the pedagogic resonance (the bridge between teacher knowledge and student learning), which is critical for motivating students to learn meaningfully. Moreover, Cmaps with errors are also amenable for on-line learning platforms. Future works of our research group will develop an automated process for evaluation and feedback using the task formats presented in this paper.

Natural Language Processing for Question Answering ( NLP 4 <=SEP=> The recent developments in Question Answering have kept with open-domain questions and collections, sometimes argued as being more di fficult than narrow domain-focused questions and corpora. The biomedical field is indeed a specialized domain; however, its scope is fairly broad, so that considering a biomedical QA task is not necessarily such a simplification over open-domain QA as represented in the recent TREC evaluations. We shall try to characterize salient aspects of biomedical QA as well as to give a short review of useful resources to address this task.

Guest editorial: qualitative studies in information systems: a critical review and some guiding principles <=SEP=> Please refer to attached Guest Editorial

Examining the critical success factors in the adoption of enterprise resource planning <=SEP=> This paper presents a literature review of the critical success factors (CSFs) in the implementation of enterprise resource planning (ERP) across 10 different countries/regions. The review covers journals, conference proceedings, doctoral dissertation, and textbooks from these 10 different countries/regions. Through a review of the literature, 18 CSFs were identified, with more than 80 sub-factors, for the successful implementation of ERP. The findings of our study reveal that ‘appropriate business and IT legacy systems’, ‘business plan/vision/goals/justification’, ‘business process reengineering’, ‘change management culture and programme’, ‘communication’, ‘ERP teamwork and composition’, ‘monitoring and evaluation of performance’, ‘project champion’, ‘project management’, ‘software/system development, testing and troubleshooting’, ‘top management support’, ‘data management’, ‘ERP strategy and implementation methodology’, ‘ERP vendor’, ‘organizational characteristics’, ‘fit between ERP and business/process’, ‘national culture’ and ‘country-related functional requirement’ were the commonly extracted factors across these 10 countries/regions. In these 18 CSFs, ‘top management support’ and ‘training and education’ were the most frequently cited as the critical factors to the successful implementation of ERP systems. # 2008 Elsevier B.V. All rights reserved.

Using Quality Models in Software Package Selection <=SEP=> 0 7 4 0 7 4 5 9 / 0 3 / $ 1 9 . 0 0 © 2 0 0 3 I E E E All the methodologies that have been proposed recently for choosing software packages compare user requirements with the packages’ capabilities.3–5 There are different types of requirements, such as managerial, political, and, of course, quality requirements. Quality requirements are often difficult to check. This is partly due to their nature, but there is another reason that can be mitigated, namely the lack of structured and widespread descriptions of package domains (that is, categories of software packages such as ERP systems, graphical or data structure libraries, and so on). This absence hampers the accurate description of software packages and the precise statement of quality requirements, and consequently overall package selection and confidence in the result of the process. Our methodology for building structured quality models helps solve this drawback. (See the “Related Work” sidebar for information about other approaches.) A structured quality model for a given package domain provides a taxonomy of software quality features, and metrics for computing their value. Our approach relies on the International Organization for Standardization and International Electrotechnical Commission 9126-1 quality standard,6 which we selected for the following reasons:

An AI Approach to Automatic Natural Music Transcription <=SEP=> Automatic music transcription (AMT) remains a fundamental and difficult problem in music information research, and current music transcription systems are still unable to match human performance. AMT aims to automatically generate a score representation given a polyphonic acoustical signal. In our project, we approach the AMT problem on two fronts: acoustic modeling to identify pitches from a frame of audio, and establishing a score generation model to convert exact piano roll representations of audio into more ‘natural’ sheet music. We build an end to end pipeline that aims to convert .wav classical piano audio files into a ‘natural’ score representation.

COMPARISON OF LOSSLESS DATA COMPRESSION ALGORITHMS FOR TEXT DATA <=SEP=> Data compression is a common requirement for most of the computerized applications. There are number of data compression algorithms, which are dedicated to compress different data formats. Even for a single data type there are number of different compression algorithms, which use different approaches. This paper examines lossless data compression algorithms and compares their performance. A set of selected algorithms are examined and implemented to evaluate the performance in compressing text data. An experimental comparison of a number of different lossless data compression algorithms is presented in this paper. The article is concluded by stating which algorithm performs well for text data.

A Simple and Accurate Syntax-Agnostic Neural Model for Dependency-based Semantic Role Labeling <=SEP=> We introduce a simple and accurate neural model for dependency-based semantic role labeling. Our model predicts predicate-argument dependencies relying on states of a bidirectional LSTM encoder. The semantic role labeler achieves competitive performance on English, even without any kind of syntactic information and only using local inference. However, when automatically predicted partof-speech tags are provided as input, it substantially outperforms all previous local models and approaches the best reported results on the English CoNLL2009 dataset. We also consider Chinese, Czech and Spanish where our approach also achieves competitive results. Syntactic parsers are unreliable on out-of-domain data, so standard (i.e., syntactically-informed) SRL models are hindered when tested in this setting. Our syntax-agnostic model appears more robust, resulting in the best reported results on standard out-of-domain test sets.

Walking on foot to explore a virtual environment with uneven terrain <=SEP=> In this work we examine people's ability to maintain spatial awareness of an HMD--based immersive virtual environment when the terrain of the virtual world does not match the real physical world in which they are locomoting. More specifically, we examine what happens when a subject explores a hilly virtual environment while physically walking in a flat room. In our virtual environments, subjects maintain their height (or distance to the ground plane) at all times. In the experiment described in this work, we directly compare spatial orientation in a flat virtual environment to two variations of a hilly virtual environment. Interestingly, we find that subjects' spatial awareness of the environment is improved with the addition of uneven terrain.

The emergence of lncRNAs in cancer biology. <=SEP=> The discovery of numerous noncoding RNA (ncRNA) transcripts in species from yeast to mammals has dramatically altered our understanding of cell biology, especially the biology of diseases such as cancer. In humans, the identification of abundant long ncRNA (lncRNA) >200 bp has catalyzed their characterization as critical components of cancer biology. Recently, roles for lncRNAs as drivers of tumor suppressive and oncogenic functions have appeared in prevalent cancer types, such as breast and prostate cancer. In this review, we highlight the emerging impact of ncRNAs in cancer research, with a particular focus on the mechanisms and functions of lncRNAs.

Action Reaction Learning : Analysis and Synthesis of Human Behaviour <=SEP=> We propose Action-Reaction Learning as an approach for analyzing and synthesizing human behaviour. This paradigm uncovers causal mappings between past and future events or between an action and its reaction by observing time sequences. We apply this method to analyze human interaction and to subsequently synthesize human behaviour. Using a time series of perceptual measurements, a system automatically uncovers a mapping between gestures from one human participant (an action) and a subsequent gesture (a reaction) from another participant. A probabilistic model is trained from data of the human interaction using a novel estimation technique, Conditional Expectation Maximization (CEM). The system drives a graphical interactive character which probabilistically predicts the most likely response to the user's behaviour and performs it interactively. Thus, after analyzing human interaction in a pair of participants, the system is able to replace one of them and interact with a single remaining user.

Vehicle licence plate recognition using super-resolution technique <=SEP=> Due to the development of economy and technology, the people's demands on cars are growing and so are the problems, such as finding stolen car, banning violation and parking lot management. It will be time-consuming and low-efficiency if we do those jobs only by human because of the limitation of human being's concentration. Therefore, it has been a popular topic to develop intelligent monitoring system under new video technology within a decade. There are still many rooms for future development and application in the car license detection and recognition fields. For finding stolen car, we can integrate car license detection system and road monitoring system to analyze the videos and trace the objects, so we can gain high-efficiency and low-cost results. For parking lot management system, we can have the result of access management and automatic charge to reduce the human resource through car license recognition system. Automated toll of highway can be done through car license recognition system as well. Because the car license recognition system is mostly applied to security monitoring field and business purposes, the demand of the accuracy is quite strict. There are causes which make the inaccuracy of the license recognition, such as the lack of video resolution, too small license due to the distance and the light and shadow. We will discuss the license recognition system and how to use apply the super-resolution to overcome those above problems.

PubChem Substance and Compound databases <=SEP=> PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public repository for information on chemical substances and their biological activities, launched in 2004 as a component of the Molecular Libraries Roadmap Initiatives of the US National Institutes of Health (NIH). For the past 11 years, PubChem has grown to a sizable system, serving as a chemical information resource for the scientific research community. PubChem consists of three inter-linked databases, Substance, Compound and BioAssay. The Substance database contains chemical information deposited by individual data contributors to PubChem, and the Compound database stores unique chemical structures extracted from the Substance database. Biological activity data of chemical substances tested in assay experiments are contained in the BioAssay database. This paper provides an overview of the PubChem Substance and Compound databases, including data sources and contents, data organization, data submission using PubChem Upload, chemical structure standardization, web-based interfaces for textual and non-textual searches, and programmatic access. It also gives a brief description of PubChem3D, a resource derived from theoretical three-dimensional structures of compounds in PubChem, as well as PubChemRDF, Resource Description Framework (RDF)-formatted PubChem data for data sharing, analysis and integration with information contained in other databases.