Infrared moving object detection based on local saliency and sparse representation |
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Institution: | 1. School of Software Engineering, South China University of Technology, Guangzhou 510006, China;2. West Anhui Unversity, Anhui 237012, China;1. National Engineering Research Center for E-Learning, Central China Normal University, Wuhan 430079, China;2. School of Computer and Information Engineering, Zhejiang Gongshang University, Hangzhou 310018, China;3. Zhejiang Lab, Hangzhou 310018, China |
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Abstract: | The key issue of infrared object detection is to locate moving object in image sequence. In order to improve detection precision, an infrared object detection method based on local saliency and sparse representation is proposed in this paper. Motion information, such as velocity, acceleration components are added into the eigenvectors to build local saliency model. And the approximate position of the infrared target is located based on the local saliency. To accurately extract the infrared object, sparse representation is used to capture complete edge of the object. Experiments show that the proposed method can accurately detect infrared moving objects, and has good robustness to external disturbances and dynamic background. |
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Keywords: | Infrared object detection Local saliency Sparse representation |
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