14227223
Bridging the semantic gap in sports video retrieval and summarization
One of the major challenges facing current media management systems and related applications is the so-called ''semantic gap'' between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs, with a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. We implemented an MPEG-7 compliant browsing system for semantic retrieval and summarization of sports video using the proposed algorithms.
10521248
A generic approach to simultaneous tracking and verification in video
In this paper, a generic approach to simultaneous tracking and verification in video data is presented. The approach is based on posterior density estimation using sequential Monte Carlo methods. Visual tracking, which is in essence a temporal correspondence problem, is solved through probability density propagation, with the density being defined over a proper state space characterizing the object configuration. Verification is realized through hypothesis testing using the estimated posterior density. In its most basic form, verification can be performed as follows. Given a measurement vector Z and two hypotheses H1 and H0, we first estimate posterior probabilities P(H0/Z) and P(H1/Z), and then choose the one with the larger posterior probability as the true hypothesis. Several applications of the approach are illustrated by experiments devised to evaluate its performance. The idea is first tested on synthetic data, and then experiments with real video sequences are presented, illustrating vehicle tracking and verification, human (face) tracking and verification, facial feature tracking, and image sequence stabilization.
16949052
Automatic keystone correction for smart projectors with embedded camera
We propose embedded algorithms for enabling a smart self-adjusting projector that is capable of fully automatic keystone distortion detection and correction, plus zooming and centering the image to fit a screen. The projector has an embedded camera and it automatically detects the screen and a specific pattern during self-adjustment. Proposed algorithms meet severe computational requirements of a portable projector and they exploit the physical constraints in a projector-(embedded) camera pair in a novel way in order to not compromise image quality under different usage conditions. We will demonstrate our projector system during the conference.
10610312
Semantic sports video analysis: approaches and new applications
In this paper, we show that event-based semantic analysis of sports video can be achieved through two major classes of methods: approaches using deterministic reasoning and approaches depending on probabilistic inference. Deterministic approaches depend on an explicit description of an event and an explicit representation of the event in terms of low-level aural-visual features that can be automatically detected. Probabilistic approaches are based on some proper state/transition models whose parameters are learnt through labeled training sequences. We first discuss the pros and cons of the two classes of approaches. Next, we present algorithms of these two types for a new application, automatic analysis of coaching video (which is different from sports broadcast programs that have been subject of most prior work).
12309193
Building a Chinese Shallow Parsed TreeBank for Collocation Extraction
To automatically extract Chinese collocations and build a large-scale collocation bank, we are developing a one-million-word Chinese shallow parsed treebank. The treebank can be used not only as a training set for our shallow parser, but also as processed data from which collocations are extracted. This paper presents several issues related to this on-going project, such as our definition of shallow parsing used in Chinese collocation extraction, guideline preparation, and quality control.
34801552
Profile-based event tracking
In this research, we focus on tracking topics that originate and evolve from a specific event. Intuitively, a few key elements of a target event, such as date, location, and persons involved, would be enough for making a decision on whether a test story is on-topic. Consequently, a profile-based event tracking method is proposed. We attempt to build an event profile from the given on-topic stories by robust information retrieval technologies. A feature selection metric and a recognized event clause are utilized to determine most (if not all) key semantic elements of the target event. Preliminary experiments on the TDT2 mandarin corpus show that this profile-based event tracking method is promising.
8043231
QoS-Aware Adaptive Services in Mobile Ad-Hoc Networks
Ad-hoc wireless networks consist of mobile nodes interconnected by multi-hop wireless paths. Unlike conventional wireless networks, ad-hoc networks have no fixed network infrastructure or administrative support. Because of the dynamic nature of the network topology and limited bandwidth of wireless channels, Quality-of-Service (QoS) provisioning is an inherently complex and difficult issue. In this paper, we propose a fully distributed and adaptive algorithm to provide statistical QoS guarantees with respect to accessibility of services in an ad-hoc network. In this algorithm, we focus on the optimization of a new QoS parameter of interest, service efficiency, while keeping protocol overheads to the minimum. To achieve this goal, we first theoretically derive the lower and upper bounds of service efficiency based on a novel model for group mobility, followed by extensive simulation results to verify the effectiveness of our algorithm.
3584727
Simple offset assignment in presence of subword data
Many embedded architectures support indirect addressing mode with autoincrement/autodecrement. By maximizing the use of this mode, generation of explicit instructions for performing address arithmetic can be avoided and thus reductions in code size and improvements in performance are achieved. Bartley [2] and Liao et al. [16] developed a method for finding a storage layout for program variables so that the use of autoincrement/autodecrement could be maximized. They introduced the Simple Offset Assignment (SOA) problem and solved it using a Path Cover (PC) formulation.We observe that many media and network processing applications make extensive use of subword data. Therefore, for such applications, by packing multiple subword variables into a single word, we can generate storage layouts that further reduce the cost of address arithmetic in two ways. First the need for address arithmetic is reduced as variables that are packed together share the same address. Second opportunities for using autoincrement andautodecrement instructions are increased as layouts are now possible which place a variable adjacent to more than two variables. This approach has become feasible because of the recent trend in embedded processor design which allows subword variables that are packed together to be accessed and manipulated without incurring performance penalty. We introduce the SubWord Offset Assignment (SWOA) problem and solve it using a Path Cover with Node Coalescing (PCwNC) formulation. Node coalescing corresponds to packing of multiple subword variables into a single word while path covering corresponds to placement of variables in adjacent memory locations to enable the use of autoincrement/autodecrement. We present three heuristics to solve the PCwNC problem. Experiments show that when the program is optimized for code size, the three proposed algorithms achieve 26%, 26.9% and 32% reduction in the number of static explicit address arithmetic instructions over Liao et al.'s algorithm. The algorithms also achieve 14.5%, 22.1%and 22.7% reduction in stack frame size. If the program is optimized for performance, the algorithms achieve 24.3%, 24.7% and 30.2% reduction in the dynamic instruction count of explicit address arithmetic instructions.
5295208
Bit rate reduction of H.264/AVC video coding for mobile applications
The increasing use of mobile applications requires higher compression efficiency for video coding. However, in mobile applications, the capability of the processor is limited and the channel is unreliable. Since the emerging H.264/AVC video coding standard provides superior compression performance compared to all the existing video coding standards, many research efforts concentrate on the compression efficiency of intra-frame coding in H.264/AVC. In this paper, we propose a novel algorithm to reduce the bit rate compressed by H.264/AVC intra-frame coding. We focus on the method to code the intra-frame prediction modes. Our proposed method significantly reduces the bits used to code the modes and do not change the syntax of the bit stream. Experimental results demonstrate it is effective and efficient