This paper presents algorithms to deal with problems associated with indexing high-dimensional feature vectors that characterize video data. Indexing high dimensional vectors is well known to be computationally expens...
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This paper presents algorithms to deal with problems associated with indexing high-dimensional feature vectors that characterize video data. Indexing high dimensional vectors is well known to be computationally expensive. Our solution is to optimally split the high dimensional vector into a few low dimensional feature vectors and querying the system for each feature vector. This involves solving an important sub-problem: developing a model of retrieval that enables us to query the system efficiently. Once we formulate the retrieval problem in terms of a retrieval model, we present an optimality criterion to maximize the number of results using this model. The criterion is based on a novel idea of using the underlying probability distribution of the feature vectors. A branch-and-prune strategy optimized per each query, is developed. This uses the set of features derived from the optimality criterion. Our results show that the algorithm performs well, giving a speedup of a factor of 25 with respect to a linear search while retaining the same level of Recall.
Multimedia Information Systems are experiencing a tremendous growth as a direct consequence of the popularity and pervasive use of world wide web. As a consequence, it is becoming increasingly important to provide eff...
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Multimedia Information Systems are experiencing a tremendous growth as a direct consequence of the popularity and pervasive use of world wide web. As a consequence, it is becoming increasingly important to provide efficient and flexible solutions for accessing and retrieving multimedia data. images and video are emerging as significant data types in multimedia systems. And yet, most commercial systems are still text and key-word based and do not fully exploit the image content of these systems. We believe that there is an opportunity to build a novel interactive multimedia system for some specific applications in electronic commerce. In this paper we present an overview of our approach, the rationale behind it and the problems that are inherent in building such a system. We address some of the technical issues in representing and analysing image primitive features. These are the building blocks of any such systems. They can be generalized into a much broader range of applications as well.
For the last few years, shot boundary detection has been recognized as an important research issue on videoretrieval. Also as a preliminary step for the task, it is essential to extract salient features from videos. ...
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For the last few years, shot boundary detection has been recognized as an important research issue on videoretrieval. Also as a preliminary step for the task, it is essential to extract salient features from videos. Recently, it has become common to perform the two tasks in compressed domain to alleviate their computational costs. In this paper, we propose novel shot boundary detection technique, which uses two feature images, or DC and edge images, extracted directly from MPEG compressed video. While a DC image can be easily obtained, edge image extraction usually requires considerable computational burden. For fast edge image extraction, we suggest to utilize only a few AC coefficients of each DCT block in motion compensated P-frames and B-frames as well as I-frames. This drastically reduces the computational burden compared to edge extraction in the spatial domain. In order to further reduce the computational burden, another edge image extraction technique is also suggested on the basis of AC prediction using DC images. By using the edge energy diagram obtained from edge images and histograms from DC images, shot boundaries such as abrupt transitions, fades, and dissolves are detected automatically. Simulation results show that the proposed techniques are fast and effective.
This paper introduces a model of spatio-temporal database that we are developing to query interesting events in video sequences. The database that we are designing is pushing the state of the art for a number of field...
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This paper introduces a model of spatio-temporal database that we are developing to query interesting events in video sequences. The database that we are designing is pushing the state of the art for a number of fields, and there are many issues that are still waiting a satisfactory solution. In this paper we present our (albeit still partial) answer to some of these problems, and the future directions of our work. Our design is divided in two layers: a Logbook which operates as a short time repository of unsummarized and unprocessed data, and a long term spatio-temporal database which stores and queries summarized data.
In this paper we address the problem of choosing appropriate features to describe the content of still pictures or video sequences including audio. As the computational analysis of these features is often time-consumi...
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In this paper we address the problem of choosing appropriate features to describe the content of still pictures or video sequences including audio. As the computational analysis of these features is often time-consuming it is useful to identify a minimal set allowing for an automatic classification of some class or genre. Further it can be shown that deleting the coherence of the features characterizing some class is not suitable to guarantee an optimal classification result. The central question of the paper is thus which features should be selected and how they should be weighted to optimize a classification problem.
With the currently existing shot change detection algorithms, abrupt changes are detected fairly well. It is thus more challenging to detect gradual changes including fades, dissolves, and wipes as these are often mis...
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With the currently existing shot change detection algorithms, abrupt changes are detected fairly well. It is thus more challenging to detect gradual changes including fades, dissolves, and wipes as these are often missed or falsely detected. In this paper, we focus on the detection of wipes. The proposed algorithm begins by processing the visual rhythm, a portion of the DC image sequence. It is a single image, a sub-sampled version of a full video in which the sampling is performed in a pre-determined and in a systematic fashion. The visual rhythm contains distinctive patterns or visual features for many different types of video effects. The different video effects manifest themselves differently on the visual rhythm. In particular, wipes appear as curves that run from the top to the bottom of the visual rhythm. Thus, using the visual rhythm, it becomes possible to automatically detect wipes simply by determining various lines and curves on the visual rhythm.
We developed a content based retrieval scheme for texture by using text based description. The texture technique is based on our previous work which uses very simple texture primitives such as edges and plain regions ...
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We developed a content based retrieval scheme for texture by using text based description. The texture technique is based on our previous work which uses very simple texture primitives such as edges and plain regions to generate features. Other methods that apply complicated statistics can be difficult to transcribe into understandable forms for normal users. Unlike these other methods, with the simplicity of our features, we can express them in terms of simple language. Hence we can bridge the gap between semantics and computed features. A number of benefits can be achieved which opens a new horizon for content based retrieval with texture. For example, the user can request a texture image without necessarily knowing what types of textures are stored. In this paper we describe the method of translating such features and the partial weighted Euclidean distance matching which allows users to describe only the parts that they are interested in. This allows them to gradually refine their texture descriptions.
A key aspect of imageretrieval using color, is the creation of robust and efficient indices. In particular, the color histogram remains the most popular index, due primarily to its simplicity. However, the color hist...
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A key aspect of imageretrieval using color, is the creation of robust and efficient indices. In particular, the color histogram remains the most popular index, due primarily to its simplicity. However, the color histogram has a number of drawbacks. Specifically, histograms capture only global activity, they require quantization to reduce dimensionality, are highly dependent on the chosen color space, have no means to exclude a certain color from a query and can provide erroneous results due to gamma nonlinearity. In this paper we present a vector angular distance measure which is implemented as part of our database system. Our system does away with histogram techniques for color indexing and retrieval and instead implements color vector techniques. We use color segmentation to extract regions of prominent color and use representative vectors from these extracted regions in the image indices. This way we end up with a much smaller index which does not have the granularity of a histogram. Instead similarity is based on our vector angular distance measure between a query color vector and the indexed representative vectors.
This article describes the use of gesture recognition techniques in computer vision as a natural interface for video content navigation, and the design of a navigation and browsing system that caters to these natural ...
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This article describes the use of gesture recognition techniques in computer vision as a natural interface for video content navigation, and the design of a navigation and browsing system that caters to these natural means of computer-human interaction. For consumer applications, video content navigation presents two challenges: (1) how to parse and summarize multiple video streams in an intuitive and efficient manner, and (2) what type of interface will enhance the ease of use for video browsing and navigation in a living room setting or an interactive environment. In this paper, we address the issues and propose the techniques that combine video content navigation with gestures, seamlessly and intuitively, in an integrated system. The current framework can incorporate speech recognition technology. We present a new type of browser for browsing and navigating video content, as well as a gesture recognition interface for this browser.
In this paper we propose a method for tracking a video object in an ordered sequence of two-dimensional images, where the outcome is the trajectory of the video object throughout the time sequence of images. This meth...
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In this paper we propose a method for tracking a video object in an ordered sequence of two-dimensional images, where the outcome is the trajectory of the video object throughout the time sequence of images. This method is designed to run in real-time in a synchronous video collaboration environment, and used for producing dynamic object annotations for enhanced video content understanding. A dynamic object is an object whose location or size in the video frame constantly changes due to the camera motion, the motion of its own, or both. We suggest a novel method for finding the trajectory of the object in the intermediate frames given the locations and shapes of the object in two end frames. In addition to the shape and location information of the object, its texture information in the end frames is used to predict the location and search space of it in the intermediate frames.
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