Statistical Modeling for Motion-based Video Classification and Retrieval
نویسندگان
چکیده
We have developed an original approach for content-based video indexing and retrieval. By introducing a causal Gibbsian modeling of the spatio-temporal distribution of appropriate local motion-related measurements, we have designed a general and efficient statistical framework for non parametric motion modeling, motion recognition and classification, and motion segmentation. It is exploited for motionbased video indexing and video retrieval for both global and partial queries by example.
منابع مشابه
Statistical Motion-Based Object Indexing Using Optic Flow Field
In this paper, we propose an original approach for content-based video indexing and retrieval. It relies on the tracking of entities of interest and the analysis of their apparent motion. To characterize the dynamic information attached to these objects, we consider a probabilistic modeling of the spatio-temporal distribution of the optic flow field computed within the tracked area after cancel...
متن کاملContent based Video Retrieval, Classification and Summarization: The State-of-the-Art and the Future
This chapter provides an overview of different video content modeling, retrieval and classification techniques employed in existing content-based video indexing and retrieval (CBVIR) systems. Based on the modeling requirements of a CBVIR system, we analyze and categorize existing modeling approaches. Starting with a review of video content modeling and representation techniques, we study view-i...
متن کاملVideo Subject Inpainting: A Posture-Based Method
Despite recent advances in video inpainting techniques, reconstructing large missing regions of a moving subject while its scale changes remains an elusive goal. In this paper, we have introduced a scale-change invariant method for large missing regions to tackle this problem. Using this framework, first the moving foreground is separated from the background and its scale is equalized. Then, a ...
متن کاملMotion-Based Feature Extraction and Ascendant Hierarchical Classification for Video Indexing and Retrieval
This paper describes an original approach for motion characterization with a view to content-based video indexing and retrieval. A statistical analysis of temporal cooccurrence distributions of relevant local motion-based measures is exploited to compute global motion de-scriptors, which allows to handle diverse motion situations. These features are used in an ascendant hierarchical classiicati...
متن کاملAn Improved Motion Vector Estimation Approach for Video Error Concealment Based on the Video Scene Analysis
In order to enhance the accuracy of the motion vector (MV) estimation and also reduce the error propagation issue during the estimation, in this paper, a new adaptive error concealment (EC) approach is proposed based on the information extracted from the video scene. In this regard, the motion information of the video scene around the degraded MB is first analyzed to estimate the motion type of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2001