Improved refinement search for H.263 to H.264/AVC transcoding based on the minimum cost tendency search
An improved refinement search method for transcoding from H.263 to H.264/AVC is proposed in this paper. Many existing motion re-estimation methods refine the input motion vector (MV) with a small search range, which is usually input MV biased. Motion estimation (ME) in H.263 usually does not consider the rate required for coding the MV, and hence, the input MV may incur a large cost in H.264/AVC. To overcome this problem, we introduce a refinement search method, called minimum cost tendency search (MCTS), which takes the difference between the cost functions for ME in H.263 and H.264/AVC into consideration. The input MV and the predictor MV are used as two anchor points. The proposed MCTS starts searching from the anchor point with a higher cost to another. Finally, the best point is chosen as the center for further refinement. The performance of MCTS is evaluated by comparing with full search, FME in JM software and refinement scheme using small diamond pattern around the input MV (RSD). Experimental results show the proposed MCTS performs more stable than FME and RSD over a wide range of output video quality

title: Lateral error recovery for application-level multicast
abstract: We consider the delivery of reliable and streaming services using application-level multicast (ALM) by means of UDP, where packet loss has to be recovered via retransmission in a timely manner in order to offer high level of service. Since packets may be lost due to congestion, tree-reconfiguration or node failure, the traditional "vertical" recovery, whereby upstream nodes retransmit the lost packet is no longer effective. We therefore propose and investigate lateral error recovery (LER). In LER, hosts are divided into a number of planes, each of which forms an independent ALM tree. Since the correlation of error among the planes is likely to be low, a node can effectively recover its error "laterally" from nearby nodes in other planes. We employ the technique of global network positioning (GNP) to map the hosts into a coordinate space and identify a set of close neighbors for error recovery by constructing a Voronoi diagram for each plane. We present centralized and distributed algorithm on how to construct the Voronoi diagrams. Using Internet-like topologies, we show via simulations that our system achieves low overheads in terms of relative delay penalty and physical link stress. For reliable service, lateral recovery greatly reduces the average recovery time as compared with vertical recovery schemes. For streaming applications, LER achieves much lower residual loss rate under a certain deadline constraint.

title: A new motion compensation approach for error resilient video coding
abstract: Multihypothesis motion-compensated prediction (MHMCP) can be used as an error resilience technique for video coding. Motivated by MHMCP, we propose a new error resilience approach named alternative motion-compensated prediction (AMCP), where two-hypothesis and one-hypothesis predictions are alternatively used with some mechanism. Both theory and simulation results show that in case of one frame loss, the expected converged error using AMCP is smaller than that using two-hypothesis MCP.

title: A Cost-Based Evaluation of End-to-End Network Measurements in Overlay Multicast
abstract: Application-layer multicast (ALM, or overlay multicast) has been proposed to overcome limitations in IP multicast. While much measurement work (such as delay or connectivity measurement) has been conducted to build efficient ALM trees, several interesting questions therein are left unclear: (1) What are the measurement costs of the different measurement methods? (2) What is the major improvement to an ALM tree by using a certain measurement method? (3) To achieve the target tree performance, what is the most cost-efficient measurement method? In this paper, we study three representative measurement methods, i.e., delay measurement, connectivity measurement and available bandwidth measurement. We select six typical ALM protocols each adopting at least one of the measurement methods and evaluate their performance on Internet-like topologies. Our study shows that delay and connectivity measurements can effectively reduce end-to-end delay in overlay trees with low measurement costs. Only using delay measurement may lead to a tree consuming much network resource. The use of connectivity and bandwidth measurements can build a tree with low resource consumption.

title: Three-loop temporal interpolation for error concealment of MDC
abstract: Multiple description coding (MDC) can be used as an error resilience (ER) technique for video coding. In case of transmission errors, error concealment can be combined with MDC to reconstruct the lost frame, such that the propagated error to the following frames is reduced. In this paper, we propose a new temporal error concealment method named three-loop temporal interpolation (TLTI). TLTI can be well combined with temporal sub-sampling ER methods, such as MDC and alternative motion-compensated prediction. In the simulation, we compare the performance of TLTI with unidirectional motion compensated temporal interpolation (UMCTI). Both visual and quantitive results show that TLTI can achieve a better video quality than UMCTI

title: A solid modeling library for the World Wide Web
abstract: A library of functions for the creation, manipulation, and viewing of solid models was created for deployment on the World Wide Web. The core data structure was based on the halfedge boundary-representation data structure proposed by M. Mantyla but much functionality had been added. It provided an alternate, constructive-solid-geometry interface to the core data structure. It was initially implemented in C and subsequently re-implemented in Java. An interface to the STEP standard and various applications such as a simple solid modeling applet, a conic illustrator applet, and a virtual furniture showroom applet had been built. It is being extended to support multiple simultaneous users as part of a prototype WWW-based tele-processing manufacturing system.

title: Accessing Hidden Web Documents by Metasearching a Directory of Specialty Search Engines
abstract: Many valuable Web documents have not been indexed by general search engines and are only accessible through specific search interfaces. Metasearching groups of specialty search engines is one possible way to gain access to large amount of such hidden Web resources. One of the key issues for returning quality metasearch results is how to select the most relevant specialty search engines for a given query. We introduce a method for categorizing specialty search engines automatically into a hierarchical directory for metasearching. By utilizing the directory, specialty search engines that have a high possibility of having relevant information and resources can be easily selected by a metasearch engine. We evaluate our algorithm by comparing the directory built by the proposed algorithm with another one that was built by human-judgments. In addition, we present a metasearch engine prototype, which demonstrates that such a specialty search engine directory can be beneficial in locating essential but hidden Web resources.

title: Sentiment-based search in digital libraries
abstract: Several researchers have developed tools for classifying/ clustering Web search results into different topic areas (such as sports, movies, travel, etc.), and to help users identify relevant results quickly in the area of interest. This study follows a similar approach, but is in the area of sentiment classification - automatically classifying on-line review documents according to the overall sentiment expressed in them. This paper presents a prototype system that has been developed to perform sentiment categorization of Web search results. It assists users to quickly focus on recommended (or non-recommended) information by classifying Web search results into four categories: positive, negative, neutral, and non-review documents, by using an automatic classifier based on a supervised machine learning algorithm, support vector machine (SVM)

title: Hypertext-assisted video indexing and content-based retrieval
abstract: An effective approach has been designed for the construction of on-line educational video systems. We have made use of the assistance of HTML text for accurate video parsing and complete content extraction. A video system with segmentation/indexing module and browsing/query modules are implemented to demonstrate the idea.

title: Semantic Analysis of Basketball Video Using Motion Information
abstract: This paper presents a new method for extracting semantic information from basketball video. Our approach consists of three stages: shot and scene boundary detection, scene classification and semantic video analysis for event detection. The scene boundary detection algorithm is based on both visual and motion prediction information. After the shot and scene boundary detection, a set of visual and motion features are extracted from scene or shot. The motion features, describing the total motion, camera motion and object motion within the scene respectively, are computed from the motion vector of the compressed video using an iterative algorithm with robust outlier rejection. Finally, the extracted features are used to differentiate offensive/defensive activities in the scenes. By analyzing the offensive/defensive activities, the positions of potential semantic events, such as foul and goal, are located. Experimental results demonstrate the effectiveness of the proposed method.