A novel Snake model with region information is proposed to detect and track moving objects. Generally, the region-information-based approach is sensitive to illumination changes and small movement in the background, w...A novel Snake model with region information is proposed to detect and track moving objects. Generally, the region-information-based approach is sensitive to illumination changes and small movement in the background, while the edge-information-based approach often obtains incorrect results for ambiguous images. The two types of information are introduced in computing the image force. Edge-information-based features make the algorithm fast and robust, and region information makes the active confour energy function obtains correct results for ambiguous images. Furthermore, an automatic contour initialization method using double difference images is given to meet the requirement of video sequence tracking. Meanwhile, a simple forecast section is added to estimate the position of the contour in the algorithm so that it can improve the convergence speed of the active contour. Experimental results show that the computation time of the algorithm is less than 0.1 s/frame. And it can be applied to a real-time system.展开更多
In this paper, we propose a video searching system that utilizes face recognition as searching indexing feature. As the applications of video cameras have great increase in recent years, face recognition makes a perfe...In this paper, we propose a video searching system that utilizes face recognition as searching indexing feature. As the applications of video cameras have great increase in recent years, face recognition makes a perfect fit for searching targeted individuals within the vast amount of video data. However, the performance of such searching depends on the quality of face images recorded in the video signals. Since the surveillance video cameras record videos without fixed postures for the object, face occlusion is very common in everyday video. The proposed system builds a model for occluded faces using fuzzy principal component analysis(FPCA), and reconstructs the human faces with the available information. Experimental results show that the system has very high efficiency in processing the real life videos, and it is very robust to various kinds of face occlusions. Hence it can relieve people reviewers from the front of the monitors and greatly enhances the efficiency as well. The proposed system has been installed and applied in various environments and has already demonstrated its power by helping solving real cases.展开更多
文摘A novel Snake model with region information is proposed to detect and track moving objects. Generally, the region-information-based approach is sensitive to illumination changes and small movement in the background, while the edge-information-based approach often obtains incorrect results for ambiguous images. The two types of information are introduced in computing the image force. Edge-information-based features make the algorithm fast and robust, and region information makes the active confour energy function obtains correct results for ambiguous images. Furthermore, an automatic contour initialization method using double difference images is given to meet the requirement of video sequence tracking. Meanwhile, a simple forecast section is added to estimate the position of the contour in the algorithm so that it can improve the convergence speed of the active contour. Experimental results show that the computation time of the algorithm is less than 0.1 s/frame. And it can be applied to a real-time system.
基金supported by the National Natural Science Foundation of China(No.61502256)
文摘In this paper, we propose a video searching system that utilizes face recognition as searching indexing feature. As the applications of video cameras have great increase in recent years, face recognition makes a perfect fit for searching targeted individuals within the vast amount of video data. However, the performance of such searching depends on the quality of face images recorded in the video signals. Since the surveillance video cameras record videos without fixed postures for the object, face occlusion is very common in everyday video. The proposed system builds a model for occluded faces using fuzzy principal component analysis(FPCA), and reconstructs the human faces with the available information. Experimental results show that the system has very high efficiency in processing the real life videos, and it is very robust to various kinds of face occlusions. Hence it can relieve people reviewers from the front of the monitors and greatly enhances the efficiency as well. The proposed system has been installed and applied in various environments and has already demonstrated its power by helping solving real cases.
