A new motion detection algorithm based on Σ– Δ background estimation
Motion detection using a stationary camera can be done by estimating the static scene (background). In that purpose, we propose a new method based on a simple recursive non linear operator, the Σ– Δ filter. Used along with a spatiotemporal regularization algorithm, it allows robust, computationally...
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| Published in | Pattern recognition letters Vol. 28; no. 3; pp. 320 - 328 |
|---|---|
| Main Authors | , |
| Format | Journal Article Conference Proceeding |
| Language | English |
| Published |
Amsterdam
Elsevier B.V
01.02.2007
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0167-8655 1872-7344 1872-7344 |
| DOI | 10.1016/j.patrec.2006.04.007 |
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| Abstract | Motion detection using a stationary camera can be done by estimating the static scene (background). In that purpose, we propose a new method based on a simple recursive non linear operator, the
Σ–
Δ filter. Used along with a spatiotemporal regularization algorithm, it allows robust, computationally efficient and accurate motion detection. To deal with complex scenes containing a wide range of motion models with very different time constants, we propose a generalization of the basic model to multiple
Σ–
Δ estimation. |
|---|---|
| AbstractList | Motion detection using a stationary camera can be done by estimating the static scene (background). In that purpose, we propose anew method based on a simple recursive non linear operator, the Sigma-Delta filter. Used along with a spatiotemporal regularization algorithm,it allows robust, computationally efficient and accurate motion detection. To deal with complex scenes containing a wide range of motionmodels with very different time constants, we propose a generalization of the basic model to multiple Sigma-Delta estimation. Motion detection using a stationary camera can be done by estimating the static scene (background). In that purpose, we propose a new method based on a simple recursive non linear operator, the Σ– Δ filter. Used along with a spatiotemporal regularization algorithm, it allows robust, computationally efficient and accurate motion detection. To deal with complex scenes containing a wide range of motion models with very different time constants, we propose a generalization of the basic model to multiple Σ– Δ estimation. |
| Author | Manzanera, Antoine Richefeu, Julien C. |
| Author_xml | – sequence: 1 givenname: Antoine surname: Manzanera fullname: Manzanera, Antoine email: antoine.manzanera@ensta.fr – sequence: 2 givenname: Julien C. surname: Richefeu fullname: Richefeu, Julien C. email: julien.richefeu@ensta.fr |
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| Keywords | Background estimation Motion detection Recursive filtering Motion estimation Image processing Recursive method Signal processing Motion detection: Background estimation Algorithm Non linear operator |
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| SubjectTerms | Applied sciences Background estimation Computer Science Computer Vision and Pattern Recognition Detection, estimation, filtering, equalization, prediction Exact sciences and technology Image Processing Information, signal and communications theory Miscellaneous Motion detection Recursive filtering Signal and communications theory Signal processing Signal, noise Telecommunications and information theory |
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| Title | A new motion detection algorithm based on Σ– Δ background estimation |
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