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Research on Video Object Tracking with C-SIFT Agorithm

Author: KangKai
Tutor: ZhouShangBo
School: Chongqing University
Course: Computer System Architecture
Keywords: Video target tracking SIFT Image registration Image Enhancement Kalman filtering
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 137
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Abstract


Important research in the field of computer vision, video object tracking, video object tracking in a video sequence to find the most similar to the contents of the specified target to detect, identify, extract and track, obtained by analyzing the the position, velocity and trajectory of the moving target, and other parameters. Video target tracking in human-computer interaction, video surveillance, intelligent building and defense industry has a wide range of applications. As a country with a wide range of research significance areas, target tracking based on computer vision has attracted the participation of a large number of scholars at home and abroad, but idealized video tracking technology is far from mature, how stable, fast, real-time tracking of the target is still challenging subject. Papers around the fast moving target tracking problem and propose a new tracking algorithm based image registration coordinate position (C-SIFT), in-depth study of C-SIFT algorithm in moving target tracking, and the main content of the paper obtained The results are as follows: ① The papers discuss in depth the status and characteristics of the video target tracking technology, including several common tracking algorithm, the tracking process and technology requirements, target tracking performance needs, and discuss a variety of target tracking algorithm, the advantages and disadvantages . ② paper focuses on the image matching SIFT (Seale Invariant Feature Transform Scale Invariant Feature Transform) the nature and role of the algorithm, a detailed discussion of how to improve the SIFT algorithm and how to to use SIFT coordinate positioning (C-SIFT, coordinate-locating of the SIFT) new algorithm for target tracking. ③ obvious for some tracking target feature points, the paper discusses the method of image pre-processing, and focuses on the two stages of image preprocessing, image enhancement and geometric correction theory and experimental verification image preprocessing technology to bring the original better image is converted to a good alignment image. Occlusion on the insufficient anti ④ for C-SIFT algorithm in target tracking applications, a C-SIFT adaptive Kalman filtering fusion target tracking algorithm. In the tracking process, the first use of the Kalman filter estimated starting iteration position of each frame, C-SIFT algorithm to get track position, then use the adaptive Kalman filter introduced shielding rate factor, regulating the Kalman filter parameters so that the C-SIFT tracking algorithm having the estimated capability of the moving target object successor state, in order to achieve a target short occlusion can also for accurate tracking of the target. By experimental validation of the algorithm detection and continuous tracking of a moving object in the video, there is robust for occlusion.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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