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.
this paper proposes an imageretrieval system which searches a database for images similar to a target imagined by a user. the system uses image features, rather than keywords, and retrieves images by reducing a multi...
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this paper proposes an imageretrieval system which searches a database for images similar to a target imagined by a user. the system uses image features, rather than keywords, and retrieves images by reducing a multidimensional feature space generated by the image feature vectors. First, the system presents the user some sample images with a suitable feature vector value and requires the user's interaction to obtain information on which image is similar to the target he/she has in his/her mind. then, the information is used to appropriately reduce the feature space. this process is continued until the target region is reduced to a suitable volume. Since this method requires neither real target image nor keywords in retrieving, it is quite simple and practical. Experimental results show the advantage and efficiency of the proposed system.
Withthe abstraction of digital video as the corresponding binary video- a process which upon numerous subjective experimentation seems to preserve (most of the) intelligibility of video content- we can pursue a preci...
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Withthe abstraction of digital video as the corresponding binary video- a process which upon numerous subjective experimentation seems to preserve (most of the) intelligibility of video content- we can pursue a precise and analytic approach to (digital videostorage and retrieval) algorithm design that are based upon geometrical (morphological) intuition. the foremost and tangible general benefit of such abstraction, however, is the immediate reductions of both data and computational complexities involved in implementing various algorithms and databases. the general paradigm presented may be utilized to address all issues pertaining to video library construction including visualization, optimum feedback query generation, object recognition, e.t.c., but the primary focus of attention in this paper are the ones pertaining to detection of fast (including presence of flashlights) and gradual scene changes (such as dissolves, fades, and various special effects such as wipes). Upon simulation we observed that we can achieve performances comparable to those of others with drastic reductions in bothstorage and computational complexities. Furthermore, since the conversion from grayscale to binary videos can be performed directly (with minimal additional computation) in the compressed domain by thresholding on the DCT DC coefficients themselves (or by using the contour information attached to MPEG4 formats), the algorithms presented herein are ideally suited for performing fast (on-the-fly) determinations of scene change, object recognition and/or tracking, and other more intelligent tasks traditionally requiring heavy demand on computational and/or storage complexities. the fast determinations may then be used on their own merits or can be used in conjunction or complementation with other higher-layer information in the future.
While current approaches for video segmentation and indexing are mostly focused on visual information, audio signals may actually play a primary role in video content parsing. In this paper, we present an approach for...
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While current approaches for video segmentation and indexing are mostly focused on visual information, audio signals may actually play a primary role in video content parsing. In this paper, we present an approach for automatic segmentation, indexing, and retrieval of audiovisual data based on audio content analysis. the accompanying audio signal of audiovisual data is first segmented and classified into basic types, i.e. speech, music, environmental sound, and silence. this coarse-level segmentation and indexing step is based on morphological and statistical analysis of several short-term features of the audio signals. then, environmental sounds are classified into finer classes such as applause, explosion, bird's sound, etc. this fine-level classification and indexing step is based on time-frequency analysis of audio signals and the use of hidden Markov model (HMM) as the classifier. On top of this archiving scheme, an audiovisual data retrieval system is proposed. Experimental results show that the proposed approach has an accuracy rate higher than 90% for the coarse-level classification, and higher than 85% for the fine-level classification. Examples of audiovisual data segmentation and retrieval are also provided.
Recent research on imagedatabases has been aimed at the development of content-based retrieval techniques for the management of visual information. Compared with such visual information as color, texture, and spatial...
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Recent research on imagedatabases has been aimed at the development of content-based retrieval techniques for the management of visual information. Compared with such visual information as color, texture, and spatial constraints, shape is so important a feature associated withthose image objects of interest that shape alone may be sufficient to identify and classify an object completely and accurately. this paper presents a novel method based on feature point histogram indexing for object shape representation in imagedatabases. In this scheme, the feature point histogram is obtained by discretizing the angles produced by the Delaunay triangulation of a set of unique feature points which characterize object shape in the context, and then counting the number of times each discrete angle occurs in the resulted triangulation. the proposed shape representation technique is translation, scale, and rotation independent. Our various experiments concluded that the Euclidean distance performs very well as the similarity measure function in combination withthe feature point histogram computed by counting the two largest angles of each individual Delaunay triangle. through the further experiment, we also found evidence that an image object representation using a feature point histogram provides an effective cue for image object discrimination.
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 retrievalthat 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.
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.
the Fractal Transform (FT) was originally introduced as a methodology for compressing digital images and representing them at different scales. the process of calculating an FT generates a great deal of information ab...
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the Fractal Transform (FT) was originally introduced as a methodology for compressing digital images and representing them at different scales. the process of calculating an FT generates a great deal of information about the affine similarities and dissimilarities of an image, most of which is discarded in compression applications. In this paper we introduce the concept of Fractal Transform Analysis and use it to derive new image descriptors. We present results of experiments in which description schemes comprised of some of these FT-based descriptors are applied to the problems of finding objects in an image similar to a given object, of indexing images, and of querying an image database consisting of about 17,000 images. Complexity and timing data are also presented.
Withthe 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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Withthe 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.
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