If a somewhat fast moving object exists in a complicated tracking environment, snake's nodes may fall into the inaccurate local minima. We propose a mean shift snake algorithm to solve this problem. However, if th...If a somewhat fast moving object exists in a complicated tracking environment, snake's nodes may fall into the inaccurate local minima. We propose a mean shift snake algorithm to solve this problem. However, if the object goes beyond the limits of mean shift snake module operation in suc- cessive sequences, mean shift snake's nodes may also fall into the local minima in their moving to the new object position. This paper presents a motion compensation strategy by using particle filter; therefore a new Particle Filter Mean Shift Snake (PFMSS) algorithm is proposed which combines particle filter with mean shift snake to fulfill the estimation of the fast moving object contour. Firstly, the fast moving object is tracked by particle filter to create a coarse position which is used to initialize the mean shift algorithm. Secondly, the whole relevant motion information is used to compensate the snake's node positions. Finally, snake algorithm is used to extract the exact object contour and the useful information of the object is fed back. Some real world sequences are tested and the results show that the novel tracking method have a good performance with high accuracy in solving the fast moving problems in cluttered background.展开更多
A novel contour tracking method using weighted structure tensor based variational level set is proposed in this paper.The image is first converted to weighted structure tensor field by extracting apositive definite sy...A novel contour tracking method using weighted structure tensor based variational level set is proposed in this paper.The image is first converted to weighted structure tensor field by extracting apositive definite symmetric covariance matrix for each pixel.Then,a level set method is employed to represent object contour implicitly which separates the image domain into two areas each modeled by tensor field based Gaussian mixture model separately.By solving agradient flow equation of energy functional with respect to the level set,the object contour will converge to its real profile in the newly arrived frame.Experimental results on several video sequences demonstrate the better performance of our method than the other two contour tracking algorithms.展开更多
Traditional cartoons have been widely used in entertainment,education,and advertisement.Thus,a large amount of cartoon data is available.In this paper,we propose a new technique for capturing the motion of a character...Traditional cartoons have been widely used in entertainment,education,and advertisement.Thus,a large amount of cartoon data is available.In this paper,we propose a new technique for capturing the motion of a character in an existing cartoon sequence.This technique tracks the contours of the cartoon character in the sequence,and key frames are used to guide the tracking.We model contour tracking as a space-time optimization problem in which an energy function including both temporal and spatial constraints is defined.First,the user labels the contours of the character on the key frames.Then,the contours on the intermediate frames are tracked by minimizing the energy function.The user may need to interactively adjust the tracking result and restart the optimization process to refine the result.Finally,an edge snapping algorithm is applied to make the tracking result more precise.Experiments show that our technique works effectively.展开更多
An accurate and robust approach for tracking and guiding multiple laser beams is developed, which can be applied to the task of beam and target alignment. Multiple laser spots are firstly detected and recognized from ...An accurate and robust approach for tracking and guiding multiple laser beams is developed, which can be applied to the task of beam and target alignment. Multiple laser spots are firstly detected and recognized from the image sequences of the target and laser spots. Then, the contour tracking algorithm based on the chain code is investigated, in which the shape matching scheme based on the invariant moments is employed to distinguish different spots. When occlusion occurs in the multiple spots tracking procedure,the contour tracking combined with Kalman filter prediction is proposed to obtain the positions of multiple spots in real-time. In order to guide 3 spots to align the target, an incremental proportional integral(PI) controller is employed to make the image features of spots converge to the desired ones. Comparative experiments show that, the proposed tracking method can successfully cope with the fast motion, partial or complete occlusion. The experiment results on spots guiding also exhibit the accurate and robust performance of the strategy. The proposed visual system solves the problem of spots mixing, reduces the alignment time, improves the shooting accuracy and has been successfully applied to the experimental platform.展开更多
基金Supported by the National Natural Science Foundation of China (No. 60672094)
文摘If a somewhat fast moving object exists in a complicated tracking environment, snake's nodes may fall into the inaccurate local minima. We propose a mean shift snake algorithm to solve this problem. However, if the object goes beyond the limits of mean shift snake module operation in suc- cessive sequences, mean shift snake's nodes may also fall into the local minima in their moving to the new object position. This paper presents a motion compensation strategy by using particle filter; therefore a new Particle Filter Mean Shift Snake (PFMSS) algorithm is proposed which combines particle filter with mean shift snake to fulfill the estimation of the fast moving object contour. Firstly, the fast moving object is tracked by particle filter to create a coarse position which is used to initialize the mean shift algorithm. Secondly, the whole relevant motion information is used to compensate the snake's node positions. Finally, snake algorithm is used to extract the exact object contour and the useful information of the object is fed back. Some real world sequences are tested and the results show that the novel tracking method have a good performance with high accuracy in solving the fast moving problems in cluttered background.
基金Supported by the National High-Tech Research & Development Program of China(2009AA01Z323)
文摘A novel contour tracking method using weighted structure tensor based variational level set is proposed in this paper.The image is first converted to weighted structure tensor field by extracting apositive definite symmetric covariance matrix for each pixel.Then,a level set method is employed to represent object contour implicitly which separates the image domain into two areas each modeled by tensor field based Gaussian mixture model separately.By solving agradient flow equation of energy functional with respect to the level set,the object contour will converge to its real profile in the newly arrived frame.Experimental results on several video sequences demonstrate the better performance of our method than the other two contour tracking algorithms.
基金Project supported by the National Natural Science Foundation of China (No.60903134)the National Key Technology R & D Program of China (No.2007BAH11B00)the Fundamental Research Funds for the Central Universities of China (No.2009QNA5021)
文摘Traditional cartoons have been widely used in entertainment,education,and advertisement.Thus,a large amount of cartoon data is available.In this paper,we propose a new technique for capturing the motion of a character in an existing cartoon sequence.This technique tracks the contours of the cartoon character in the sequence,and key frames are used to guide the tracking.We model contour tracking as a space-time optimization problem in which an energy function including both temporal and spatial constraints is defined.First,the user labels the contours of the character on the key frames.Then,the contours on the intermediate frames are tracked by minimizing the energy function.The user may need to interactively adjust the tracking result and restart the optimization process to refine the result.Finally,an edge snapping algorithm is applied to make the tracking result more precise.Experiments show that our technique works effectively.
基金supported by National Natural Science Foundation of China(Nos.61227804 and 61105036)
文摘An accurate and robust approach for tracking and guiding multiple laser beams is developed, which can be applied to the task of beam and target alignment. Multiple laser spots are firstly detected and recognized from the image sequences of the target and laser spots. Then, the contour tracking algorithm based on the chain code is investigated, in which the shape matching scheme based on the invariant moments is employed to distinguish different spots. When occlusion occurs in the multiple spots tracking procedure,the contour tracking combined with Kalman filter prediction is proposed to obtain the positions of multiple spots in real-time. In order to guide 3 spots to align the target, an incremental proportional integral(PI) controller is employed to make the image features of spots converge to the desired ones. Comparative experiments show that, the proposed tracking method can successfully cope with the fast motion, partial or complete occlusion. The experiment results on spots guiding also exhibit the accurate and robust performance of the strategy. The proposed visual system solves the problem of spots mixing, reduces the alignment time, improves the shooting accuracy and has been successfully applied to the experimental platform.