Efficient video similarity measurement with video signature
The proliferation of video content on the Web makes similarity detection an indispensable tool in Web data management, searching, and navigation. We propose a number of algorithms to efficiently measure video similarity. We define video as a set of frames, which are represented as high dimensional vectors in a feature space. Our goal is to measure ideal video similarity (IVS), defined as the percentage of clusters of similar frames shared between two video sequences. Since IVS is too complex to be deployed in large database applications, we approximate it with Voronoi video similarity (VVS), defined as the volume of the intersection between Voronoi cells of similar clusters. We propose a class of randomized algorithms to estimate VVS by first summarizing each video with a small set of its sampled frames, called the video signature (ViSig), and then calculating the distances between corresponding frames from the two ViSigs. By generating samples with a probability distribution that describes the video statistics, and ranking them based upon their likelihood of making an error in the estimation, we show analytically that ViSig can provide an unbiased estimate of IVS. Experimental results on a large dataset of Web video and a set of MPEG-7 test sequences with artificially generated similar versions are provided to demonstrate the retrieval performance of our proposed techniques.

title: Fast similarity search on video signatures
abstract: Video signatures are compact representations of video sequences designed for efficient similarity measurement. In this paper, we propose a feature extraction technique to support fast similarity search on large databases of video signatures. Our proposed technique transforms the high dimensional video signatures into low dimensional vectors where similarity search can be efficiently performed. We exploit both the upper and lower bounds of the triangle inequalities in approximating the high-dimensional metric, and combine this approximation with the classical PCA to achieve the target dimension. Experimental results on a large set of Web video sequences show that our technique outperforms fastmap, Haar wavelet, PCA, and triangle-inequality pruning.

title: Efficient video similarity measurement and search
abstract: We consider the use of meta-data and/or video-domain methods to detect similar videos on the Web. Meta-data is extracted from the textual and hyperlink information associated with each video clip. In the video domain, we apply an efficient similarity detection algorithm called video signature. The idea is to form a signature for each clip by selecting a small number of its frames that are most similar to a set of random seed images. We then apply a statistical pruning algorithm to allow fast detection on very large databases. Using a small ground-truth set, we achieve 90% recall and 95% precision using only 8% of the total number of operations required without pruning. For a database of around 46,000 video clips crawled from the Web, the video signature technique significantly outperforms meta-data in precision and recall. We show that even better performance can be achieved by combining them together. Based on our measurements, each video clip in our database has, on average, 1.53 similar copies.

title: Fast similarity search and clustering of video sequences on the world-wide-web
abstract: We define similar video content as video sequences with almost identical content but possibly compressed at different qualities, reformatted to different sizes and frame-rates, undergone minor editing in either spatial or temporal domain, or summarized into keyframe sequences. Building a search engine to identify such similar content in the World-Wide Web requires: 1) robust video similarity measurements; 2) fast similarity search techniques on large databases; and 3) intuitive organization of search results. In a previous paper, we proposed a randomized technique called the video signature (ViSig) method for video similarity measurement. In this paper, we focus on the remaining two issues by proposing a feature extraction scheme for fast similarity search, and a clustering algorithm for identification of similar clusters. Similar to many other content-based methods, the ViSig method uses high-dimensional feature vectors to represent video. To warrant a fast response time for similarity searches on high dimensional vectors, we propose a novel nonlinear feature extraction scheme on arbitrary metric spaces that combines the triangle inequality with the classical Principal Component Analysis (PCA). We show experimentally that the proposed technique outperforms PCA, Fastmap, Triangle-Inequality Pruning, and Haar wavelet on signature data. To further improve retrieval performance, and provide better organization of similarity search results, we introduce a new graph-theoretical clustering algorithm on large databases of signatures. This algorithm treats all signatures as an abstract threshold graph, where the distance threshold is determined based on local data statistics. Similar clusters are then identified as highly connected regions in the graph. By measuring the retrieval performance against a ground-truth set, we show that our proposed algorithm outperforms simple thresholding, single-link and complete-link hierarchical clustering techniques.

title: Stress Testing of Distributed Multimedia Software Systems
abstract: With the advance in network technologies, the use of distributed multimedia data has become very popular. Distributed multimedia systems are complex and error prone. While there are well established testing techniques for the functionalities of such systems, the technique of stress testing to improve test efficiency has not received much attention. It has been argued that faults are more likely to occur in situations where there is a fierce competition for resources. When the system is heavily loaded, errors like mismanagement of buffers can be easily identified. In this paper, we present several criteria for selecting test cases, and describe two methods for generating test cases which maximize system resource usage. Our approach is based on symbolic execution and constraint solving. An example is given to illustrate the concepts and techniques.

title: A Lower Bound for Permutation Routing on Two-Dimensional Bused Meshes
abstract: We prove a 0.691n lower bound for the permutation routing problem in n×n meshes with row and column buses whose propagation delay is one time unit. For meshes having non-unit-time buses, we use similar arguments to derive some simple lower bounds for the permutation routing problem.

title: A model-based authorware for the construction of distributed multimedia systems
abstract: Distributed multimedia systems typically involve a sophisticated user interaction. Further, objects are allocated on physically distributed computing systems, and multimedia data must be transferred across heterogeneous networks in a timely manner. These systems often have complex requirements on a user interaction, quality of service and temporal order among media streams. The design and implementation of these requirements are inherently complex and present an extraordinary design and programming challenge. Generally, these complex requirements cannot be adequately captured using a single model or a design notation. The challenge amounts to (i) identification of multiple, often orthogonal models, each capturing a specific aspect of the requirements, and (ii) provision of an authorware that supports the composition of these models. In this paper, we propose to capture the multimedia requirements in three different models: configuration, user control and presentation, and demonstrate how the composition of these models can be supported by an authorware using the Java and CORBA technologies. The concepts are illustrated using a real-life example based on a virtual city tour application that features distributed controls, collaborative work and multimedia presentations. Various distributed multimedia applications like video phone, video conferencing and distributed presentation have been successfully constructed using the proposed multiple models and authorware. The results are encouraging and the approach can shorten the development of multimedia applications considerably.

title: Parallel Algorithm Design for Workstation Clusters
abstract: Clusters of workstations connected by local area networks are in common use in many organizations. The combined processing power of these clusters is rarely exploited owing to the lack of suitable parallel algorithms. The paper describes a parallel programming paradigm called supervisor-worker, suitable for the workstation environment, which can be used to speed up the execution of a large class of existing sequential programs. Simple formulae are developed to predict the speed-up of a parallel algorithm developed in this way. The predictions depend on two easily-determined parameters of the sequential program and the characteristic communication cost of the workstation cluster. Consequently, it is possible to estimate the benefits of the parallel program before proceeding with detailed implementation. As an example, the parallel version of a travelling salesman program is developed and the measured speed-up compared with the predicted speed-up.

title: Modeling and Verifying Strong Cache Consistency for Mobile Data Access