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7th storage and retrieval for image and video databases conference

作者： Lienhart, R Intel Corp Microcomp Res Labs Santa Clara CA 95052 USA

ISBN: (纸本)0819431273

Various methods of automatic shot boundary detection have been proposed and claimed to perform reliably. Although the detection of edits is fundamental to any kind of video analysis since it segments a video into its basic components, the shots, only few comparative investigations on early shot boundary detection algorithms have been published. These investigations mainly concentrate on measuring the Edit detection performance, however;do not consider the algorithms' ability to classify the types and to locate the boundaries of the edits correctly. This gaper extends these comparative investigations More recent algorithms designed explicitly to detect specific complex editing operations such as fades and dissolves are taken into account and their ability to classify the types and locate the boundaries of such edits are examined. The algorithms' performance is measured in terms of hit rate, number of false hits, and miss rate for hard cuts, fades, and dissolves over a large and diverse set of video sequences. The experiments show, that while hard cuts and fades can be detected reliably, dissolves are still an open research issue The fate hit rate for dissolves is usually unacceptably high, ranging from 50% up to over 400%. Moreover;all algorithms seem to fail under roughly the same conditions.

关键词： video content analysis shot boundary detection hard cut detection fade detection dissolve detection

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Automatic soccer video analysis and summarization

Automatic soccer video analysis and summarization

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conference on storage and retrieval for Media databases 2003

作者： Ekin, A Tekalp, AM Univ Rochester Dept Elect & Comp Engn Rochester NY 14627 USA

ISBN: (纸本)0819448214

We propose a fully automatic and computationally efficient framework for analysis and summarization of soccer videos using cinematic and object-based features. The proposed framework includes some novel low-level soccer video processing algorithms, such as dominant color region detection, robust shot boundary detection, and shot classification, as well as some higher-level algorithms for goal detection, referee detection, and penalty-box detection. The system can output three types of summaries: i) all slow-motion segments in a game, ii) all goals in a game, and iii) slow-motion segments classified according to object-based features. The first two types of summaries are based on cinematic features only for speedy processing, while the summaries of the last type contain higher-level semantics. The proposed framework is efficient, effective, and robust for soccer video processing. It is efficient in the sense that there is no need to compute object-based features when cinematic features are sufficient for the detection of certain events, e.g. goals in soccer. It is effective in the sense that the framework can also employ object-based features when needed to increase accuracy (at the expense of more computation). The efficiency, effectiveness, and the robustness of the proposed framework are demonstrated over a large data set, consisting of more than 13 hours of soccer video, captured at different countries and conditions.

关键词： soccer video processing cinematic features object-based features shot classification slow-motion replay detection semantic event detection soccer video summarization

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W-TRANSFORM METHOD FOR FEATURE-ORIENTED MULTIRESOLUTION image retrieval 2

W-TRANSFORM METHOD FOR FEATURE-ORIENTED MULTIRESOLUTION IMAG...

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2nd conference on Wavelet Applications

作者： KWONG, MK LIN, BQ ARGONNE NATL LAB DIV MATH & COMP SCIARGONNEIL 60439

ISBN: (纸本)0819418447

We present a local-feature-oriented image indexing and retrieval method based on Kwong and Tang's W-transform. Multiresolution histogram comparison is an effective method for content- based image indexing and retrieval. However, most recent approaches perform multiresolution analysis for whole images but do not exploit the local features present in the images. Since W- transform is featured by its ability to handle images of arbitrary size, with no periodicity assumptions, it provides a natural tool for analyzing local image features and building indexing systems based on such features. In our approach, the histograms of the local features of images are used in the indexing system. The system not only can retrieve images that are similar or identical to the query images but also can retrieve images that contain features specified in the query images, even if the retrieved images as a whole might be very different from the query images. The local-feature-oriented method also provides a speed advantage over the global multiresolution histogram comparison method. The feature-oriented approach is expected to be applicable in managing large-scale image systems such as video databases and medical image databases.

关键词： W-TRANSFORM MULTIRESOLUTION HISTOGRAM image INDEXING AND retrieval FEATURE

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An efficient content-based video retrieval for large databases

An efficient content-based video retrieval for large databas...

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IEEE International conference on Mechatronics, Electronics and Automotive Engineering (ICMEAE)

作者： Cedillo-Hernandez, Antonio Cedillo-Hernandez, Manuel Garcia-Ugalde, Francisco Nakano-Miyatake, Mariko Perez-Meana, Hector Univ Nacl Autonoma Mexico Fac Ingn Div Ingn Elect Mexico City 04510 DF Mexico Inst Politecn Nacl Escuela Super Ingn Mecan & Elect Mexico City DF Mexico

ISBN: (纸本)9781467383295

Multimedia data grows fast due to advances in information technologies, creating the demand for efficient video indexing and object retrieval techniques. Traditional methods consume significant computational resources such as storage space and processing time. In this paper we propose an efficient content-based video retrieval system that is based on three main stages. The first stage involves computing the DC-image of each I-frame, from which a summarization process to extract key-frames is performed. During the second stage, a segmentation processes is applied to each key-frame in order to isolate the region of interest within it. Local features are extracted from the resulting area and are stored as the descriptor of the frame. The retrieval stage is carried out by computing the Euclidean distance and determines if its content is related with the video database. Experimental results show that the proposed approach is promising in terms of efficiency and effectiveness.

关键词： Efficient CBVR system video indexing DC-frame SURF

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International conference on image Processing (ICIP 2001)

作者： Cheung, SS Zakhor, A Univ Calif Berkeley Dept Elect Engn & Comp Sci Berkeley CA 94720 USA

ISBN: (纸本)0780367251

The proliferation of video content on the web makes similarity detection an indispensable tool in web data management, searching, and navigation. We have previously proposed a compact representation of video clips, called video signature, for retrieving similar video clips in large databases. In this paper we propose a new signature clustering algorithm to further improve retrieval performance. The algorithm treats all the signatures as an abstract threshold graph, where the threshold is determined based on local data statistics. Similar clusters are identified as highly connected regions in the graph. This algorithm outperforms simple thresholding and hierarchical clustering techniques in identifying a set of manually-determined similar clusters from a dataset of 46,356 web video clips. At 95% precision, our algorithm attains 85% recall while simple thresholding and complete-link hierarchical scheme attain 67% and 75% recall respectively. Applying our algorithm to the entire dataset, 6,900 similar clusters are identified, with an average cluster size of 2.81 video clips. The distribution of cluster sizes follows a power-law distribution, which has been shown to describe many web phenomena.

关键词： image processing

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Unsupervised view and rate invariant clustering of video sequences

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COMPUTER VISION AND image UNDERSTANDING 2009年第3期113卷 353-371页

作者： Turaga, Pavan Veeraraghavan, Ashok Chellappa, Rama Univ Maryland Ctr Automat Res Dept Elect & Comp Engn UMIACS College Pk MD 20742 USA

videos play an ever increasing role in our everyday lives with applications ranging from news, entertainment, scientific research, security and surveillance. Coupled with the fact that cameras and storage media are becoming less expensive, it has resulted in people producing more video content than ever before. This necessitates the development of efficient indexing and retrieval algorithms for video data. Most state-of-the-art techniques index videos according to the global content in the scene such as color, texture, brightness, etc. In this paper, we discuss the problem of activity-based indexing of videos. To address the problem, first we describe activities as a cascade of dynamical systems which significantly enhances the expressive power of the model while retaining many of the computational advantages of using dynamical models. Second, we also derive methods to incorporate view and rate-invariance into these models so that similar actions are clustered together irrespective of the viewpoint or the rate of execution of the activity. We also derive algorithms to learn the model parameters from a video stream and demonstrate how a single video sequence may be clustered into different clusters where each cluster represents an activity. Experimental results for five different databases show that the clusters found by the algorithm correspond to semantically meaningful activities. (C) 2008 Elsevier Inc. All rights reserved.

关键词： video clustering Summarization Surveillance Cascade of linear dynamical systems View invariance Affine invariance Rate invariance

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Efficient image database retrieval using wavelet packets and Principal Component Analysis

Efficient image database retrieval using wavelet packets and...

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conference on Wavelet Applications in Signal and image Processing Vii

作者： Saeed, M Rabiee, H MIT Dept Elect Engn & Comp Sci Cambridge MA 02139 USA

ISBN: (纸本)0819432997

With the advancement of multimedia technology and the internet, numerous applications have arisen which require the storage and retrieval of large image and video databases. A novel method (Eigenwavelet) was developed to retrieve images from a large heterogeneous image database upon a user-specified query. The queries are in the form of an image(s) that the user seeks to find similar matches to in the database. Using the queries, an efficient algorithm was developed which decomposed each image in the database using wavelet packet analysis. Along each node of the packet tree, Principal Component Analysis (PCA) was applied to the: database images after wavelet packet decomposition, and a set of eigenvectors were generated for each node of the packet tree. To search the image database, the query images are projected onto these eigenvectors (Eigenwavelet coefficients). A distance metric is computed between the projections of the queries and the projections of the images in the database onto the eigenwavelets. Those images with minimal distance (L1) are retrieved in response to a unique query set. Simulations with a heterogeneous image database suggest the Eigenwavelet method of image retrieval is a robust and computationally tractable method of retrieving images with a probability of detection > .8.

关键词： image retrieval wavelet packets Principal Component Analysis image metrics

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An image retrieval Approach to Setup Difficulty Levels in Training Systems for Endomicroscopy Diagnosis

An Image Retrieval Approach to Setup Difficulty Levels in Tr...

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13th International conference on Medical image Computing and Computer-Assisted Intervention (MICCAI)

作者： Andre, Barbara Vercauteren, Tom Buchner, Anna M. Shahid, Muhammad Waseem Wallace, Michael B. Ayache, Nicholas Mauna Kea Technol Paris France INRIA Asclepios Paris France Hosp Univ Penn Philadelphia PA USA Mayo Clin Jacksonville FL USA

ISBN: (纸本)9783642157448

Learning medical image interpretation is an evolutive process that requires modular training systems, from non-expert to expert users. Our study aims at developing such a system for endomicroscopy diagnosis. It uses a difficulty predictor to try and shorten the physician learning curve. As the understanding of video diagnosis is driven by visual similarities, we propose a content-based video retrieval approach to estimate the level of interpretation difficulty. The performance of our retrieval method is compared with several state of the art methods, and its genericity is demonstrated with two different clinical databases, on the Barrett's Esophagus and on colonic polyps. From our retrieval results, we learn a difficulty predictor against a ground truth given by the percentage of false diagnoses among several physicians. Our experiments show that, although our datasets are not large enough to test for statistical significance, there is a noticeable relationship between our retrieval-based difficulty estimation and the difficulty experienced by the physicians.

关键词： Diagnosis

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Indexing and retrieval of multimedia objects at different levels of granularity

Indexing and retrieval of multimedia objects at different le...

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conference on Multimedia storage and Archiving Systems iiI

作者： Faudemay, P Durand, G Seyrat, C Tondre, N Univ Paris 06 LIP6 F-75255 Paris 05 France

ISBN: (纸本)0819429880

Intelligent access to multimedia databases for "naive user" should probably be based on queries formulation by "intelligent agents". These agents should "understand" the semantics of the contents, learn user preferences and deliver to the user a subset of the source contents, while keeping the freedom of choice of the user. Such systems should interpret multimedia contents in terms of multiple audiovisual objects (from video to visual or audio object), and on actions and scenarios. In our project we have developed a method for image segmentation into semantic objects, even in the case of still images. We use this method, and user-defined collections of such objects, and to characterize stories contents. For this purpose, we also use audio information from selected parts of the video. Stories are characterized by a set of visual concepts and words, and semantic similarity between stories is evaluated based on information retrieval methods. The system learns user preferences, and incrementally builds a user profile, which is used to present relevant stories in appropriate order. This approach was used to build a mockup of a simple "plus" engine, which is presently being experimented.

关键词： multimedia indexing video analysis spatial segmentation temporal segmentation example-based retrieval

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image indexing by spatial relationships between salient objects

Image indexing by spatial relationships between salient obje...

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2011 Federated conference on Computer Science and Information Systems, FedCSIS 2011

作者： Ganea, Eugen Brezovan, Marius University of Craiova Bd. Decebal 107 Romania

ISBN: (纸本)9781457700415

In this paper, we presented our technique to extract and to use the spatial relationships between two or more salient objects. Using an object oriented hypergraph data structure, the spatial relationships are determined and stored in an object-oriented database. This work aims to unified the phases of processing, indexing and retrieval of images. The proposed model can be applicable to other types of data (video) and to semantic relations hidden in an image. The structure of the database used for image storage allow the construction of the indexes classes hierarchy in order to improve the results of image retrieval. Our method requires more experiments for datasets which come from different areas and for images which contain more salient objects. © 2011 Polish Info Processing Soc.

关键词： Object-oriented databases

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