A snake algorithm has been known that it has a strong point in extracting the exact contour of an object. But it is apt to be influenced by scattered edges around the control points. Since the shape of a moving object...A snake algorithm has been known that it has a strong point in extracting the exact contour of an object. But it is apt to be influenced by scattered edges around the control points. Since the shape of a moving object in 2D image changes a lot due to its rotation and translation in the 3D space, the conventional algorithm that takes into account slowly moving objects cannot provide an appropriate solution. To utilize the advantages of the snake algorithm while minimizing the drawbacks, this paper proposes the area variation based color snake algorithm for moving object tracking. The proposed algorithm includes a new energy term which is used for preserving the shape of an object between two consecutive images. The proposed one can also segment precisely interesting objects on complex image since it is based on color information. Experiment results show that the proposed algorithm is very effective in various environments.展开更多
Tracking moving target from image or video sequence is a hot research topic in computer vision. An algorithm based on LogGabor wavelet and Mean-shift has been proposed for moving target tracking under fixed camera set...Tracking moving target from image or video sequence is a hot research topic in computer vision. An algorithm based on LogGabor wavelet and Mean-shift has been proposed for moving target tracking under fixed camera setting and complicated environment. Phase coherency of LogGabor wavelet facilitates to extract the edge of moving target and check noise. According to the edge detection,the starting location of Mean-shift can be estimated using the target center coordinate. Eventually,a real-time moving target can be extracted by doing iterative matching pursuit,and experimental results proved the effectiveness of the method proposed.展开更多
The most important problem in targets tracking is data association which may be represented as a sort of constraint combinational optimization problem. Chaos optimization and adaptive genetic algorithm were used to de...The most important problem in targets tracking is data association which may be represented as a sort of constraint combinational optimization problem. Chaos optimization and adaptive genetic algorithm were used to deal with the problem of multi-targets data association separately. Based on the analysis of the limitation of chaos optimization and genetic algorithm, a new chaos genetic optimization combination algorithm was presented. This new algorithm first applied the "rough" search of chaos optimization to initialize the population of GA, then optimized the population by real-coded adaptive GA. In this way, GA can not only jump out of the "trap" of local optimal results easily but also increase the rate of convergence. And the new method can also avoid the complexity and time-consumed limitation of conventional way. The simulation results show that the combination algorithm can obtain higher correct association percent and the effect of association is obviously superior to chaos optimization or genetic algorithm separately. This method has better convergence property as well as time property than the conventional ones.展开更多
Smweillance system using active tracking camera has no distance limitation of surveillance range compared to supersonic or sound sensors. However, complex motion tracking algorithm requires huge amount of computation,...Smweillance system using active tracking camera has no distance limitation of surveillance range compared to supersonic or sound sensors. However, complex motion tracking algorithm requires huge amount of computation, and it often requires exfmasive DSPs or embedded processors. This paper proposes a novel motion tracking trait based on different image for fast and simple motion tracking. It uses configuration factor to avoid noise and inaccuracy. It reduces the required computation significantly, so as to be implemented on Field Programmable Gate Array（FFGAs ） instead of expensive Digital Signal Processing（DSPs）. It also performs calculation for motion estimation in video compression, so it can be easily combined with surveil system with video recording functionality based on video compression. The proposed motion tracking system implemented on Xilinx Vertex-4 FPGA can process 48 frames per second, and operating frequency of motion tracking trait is 100 MHz.展开更多
文摘A snake algorithm has been known that it has a strong point in extracting the exact contour of an object. But it is apt to be influenced by scattered edges around the control points. Since the shape of a moving object in 2D image changes a lot due to its rotation and translation in the 3D space, the conventional algorithm that takes into account slowly moving objects cannot provide an appropriate solution. To utilize the advantages of the snake algorithm while minimizing the drawbacks, this paper proposes the area variation based color snake algorithm for moving object tracking. The proposed algorithm includes a new energy term which is used for preserving the shape of an object between two consecutive images. The proposed one can also segment precisely interesting objects on complex image since it is based on color information. Experiment results show that the proposed algorithm is very effective in various environments.
文摘Tracking moving target from image or video sequence is a hot research topic in computer vision. An algorithm based on LogGabor wavelet and Mean-shift has been proposed for moving target tracking under fixed camera setting and complicated environment. Phase coherency of LogGabor wavelet facilitates to extract the edge of moving target and check noise. According to the edge detection,the starting location of Mean-shift can be estimated using the target center coordinate. Eventually,a real-time moving target can be extracted by doing iterative matching pursuit,and experimental results proved the effectiveness of the method proposed.
文摘The most important problem in targets tracking is data association which may be represented as a sort of constraint combinational optimization problem. Chaos optimization and adaptive genetic algorithm were used to deal with the problem of multi-targets data association separately. Based on the analysis of the limitation of chaos optimization and genetic algorithm, a new chaos genetic optimization combination algorithm was presented. This new algorithm first applied the "rough" search of chaos optimization to initialize the population of GA, then optimized the population by real-coded adaptive GA. In this way, GA can not only jump out of the "trap" of local optimal results easily but also increase the rate of convergence. And the new method can also avoid the complexity and time-consumed limitation of conventional way. The simulation results show that the combination algorithm can obtain higher correct association percent and the effect of association is obviously superior to chaos optimization or genetic algorithm separately. This method has better convergence property as well as time property than the conventional ones.
基金sponsored by the MKE(The Ministry of Knowledge Economy,Korea),the ITRC(Information Technology Research Center)support program(NIPA-2009-(C1090-0902-0007))the System Semiconductor Industry Development Center,Human Resource Development Project for IT SOC Architecture
文摘Smweillance system using active tracking camera has no distance limitation of surveillance range compared to supersonic or sound sensors. However, complex motion tracking algorithm requires huge amount of computation, and it often requires exfmasive DSPs or embedded processors. This paper proposes a novel motion tracking trait based on different image for fast and simple motion tracking. It uses configuration factor to avoid noise and inaccuracy. It reduces the required computation significantly, so as to be implemented on Field Programmable Gate Array（FFGAs ） instead of expensive Digital Signal Processing（DSPs）. It also performs calculation for motion estimation in video compression, so it can be easily combined with surveil system with video recording functionality based on video compression. The proposed motion tracking system implemented on Xilinx Vertex-4 FPGA can process 48 frames per second, and operating frequency of motion tracking trait is 100 MHz.
