Video object segmentation and tracking using region-based statistics
Two new region-based methods for video object tracking using active contours are presented. The first method is based on the assumption that the color histogram of the tracked object is nearly stationary from frame to frame. The proposed method is based on minimizing the color histogram difference b...
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| Veröffentlicht in: | Signal processing. Image communication 2007-11, Vol.22 (10), p.891-905 |
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| container_title | Signal processing. Image communication |
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| creator | ERDEM, Cigdem Eroglu |
| description | Two new region-based methods for video object tracking using active contours are presented. The first method is based on the assumption that the color histogram of the tracked object is nearly stationary from frame to frame. The proposed method is based on minimizing the color histogram difference between the estimated objects at a reference frame and the current frame using a dynamic programming framework. The second method is defined for scenes where there is an out-of-focus blur difference between the object of interest and the background. In such scenes, the proposed “defocus energy” can be utilized for automatic segmentation of the object boundary, and it can be combined with the histogram method to track the object more efficiently. Experiments demonstrate that the proposed methods are successful in difficult scenes with significant background clutter. |
| doi_str_mv | 10.1016/j.image.2007.09.001 |
| format | Article |
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The first method is based on the assumption that the color histogram of the tracked object is nearly stationary from frame to frame. The proposed method is based on minimizing the color histogram difference between the estimated objects at a reference frame and the current frame using a dynamic programming framework. The second method is defined for scenes where there is an out-of-focus blur difference between the object of interest and the background. In such scenes, the proposed “defocus energy” can be utilized for automatic segmentation of the object boundary, and it can be combined with the histogram method to track the object more efficiently. 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Experiments demonstrate that the proposed methods are successful in difficult scenes with significant background clutter.</description><subject>Active contours</subject><subject>Applied sciences</subject><subject>Curve evolution</subject><subject>Defocus</subject><subject>Detection, estimation, filtering, equalization, prediction</subject><subject>Exact sciences and technology</subject><subject>Histogram matching</subject><subject>Image processing</subject><subject>Information, signal and communications theory</subject><subject>Object tracking</subject><subject>Pattern recognition</subject><subject>Selective focus</subject><subject>Signal and communications theory</subject><subject>Signal processing</subject><subject>Signal, noise</subject><subject>Telecommunications and information theory</subject><issn>0923-5965</issn><issn>1879-2677</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2007</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PwzAQhi0EEqXwC1iywJZwtmM7HhgQ3xISC7Barn2pXNoEfCkS_56UVmJjuRvuee90D2OnHCoOXF8sqrTyc6wEgKnAVgB8j014Y2wptDH7bAJWyFJZrQ7ZEdECAEQNdsJu3lLEvuhnCwxDQThfYTf4IfVd4btYDNmH99TNizVtasb5OClnnjAWtOFoSIGO2UHrl4Qnuz5lr3e3L9cP5dPz_eP11VMZpK6HUqk6SmlAm0YFMFYLqUSQUc00trzVvKmtEKI2utFBBM9rY7gNXHpo2qiinLLz7d6P3H-ukQa3ShRwufQd9mtykkMNUMsRlFsw5J4oY-s-8mgofzsObmPMLdyvMbcx5sC60diYOtut9xT8ss2-C4n-orZRtuFq5C63HI6_fiXMjkLCLmBMebToYp_-vfMDF8OBGQ</recordid><startdate>20071101</startdate><enddate>20071101</enddate><creator>ERDEM, Cigdem Eroglu</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20071101</creationdate><title>Video object segmentation and tracking using region-based statistics</title><author>ERDEM, Cigdem Eroglu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c364t-554d33706785c07962352c3d5b6ef1f6184922247686c2ca147719c13a08fd5d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2007</creationdate><topic>Active contours</topic><topic>Applied sciences</topic><topic>Curve evolution</topic><topic>Defocus</topic><topic>Detection, estimation, filtering, equalization, prediction</topic><topic>Exact sciences and technology</topic><topic>Histogram matching</topic><topic>Image processing</topic><topic>Information, signal and communications theory</topic><topic>Object tracking</topic><topic>Pattern recognition</topic><topic>Selective focus</topic><topic>Signal and communications theory</topic><topic>Signal processing</topic><topic>Signal, noise</topic><topic>Telecommunications and information theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>ERDEM, Cigdem Eroglu</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Signal processing. 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| ispartof | Signal processing. Image communication, 2007-11, Vol.22 (10), p.891-905 |
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| language | eng |
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| source | Elsevier ScienceDirect Journals |
| subjects | Active contours Applied sciences Curve evolution Defocus Detection, estimation, filtering, equalization, prediction Exact sciences and technology Histogram matching Image processing Information, signal and communications theory Object tracking Pattern recognition Selective focus Signal and communications theory Signal processing Signal, noise Telecommunications and information theory |
| title | Video object segmentation and tracking using region-based statistics |
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