To track the vehicles under occlusion, a vehicle tracking algorithm based on blocks is proposed. The target vehicle is divided into several blocks of uniform size, in which the edge block can overlap its neighboring b...To track the vehicles under occlusion, a vehicle tracking algorithm based on blocks is proposed. The target vehicle is divided into several blocks of uniform size, in which the edge block can overlap its neighboring blocks. All the blocks＇ motion vectors are estimated, and the noise motion vectors are detected and adjusted to decrease the error of motion vector estimation. Then, by moving the blocks based on the adjusted motion vectors, the vehicle is tracked. Aiming at the occlusion between vehicles, a Markov random field is established to describe the relationship between the blocks in the blocked regions. The neighborhood of blocks is defined using the Euclidean distance. An energy function is defined based on the blocks＇ histograms and optimized by the simulated annealing algorithm to segment the occlusion region. Experimental results demonstrate that the proposed algorithm can track vehicles under occlusion accurately.展开更多
Image sequences processing and video encoding are extremely time consuming problems. The time complexity of them depends on image contents. This paper presents an estimation of a block motion method for video coding w...Image sequences processing and video encoding are extremely time consuming problems. The time complexity of them depends on image contents. This paper presents an estimation of a block motion method for video coding with edge alignment. This method uses blocks of size 4 × 4 and its basic idea is to find motion vector using the edge position in each video coding block. The method finds the motion vectors more accurately and faster than any known classical method that calculates all the possibilities. Our presented algorithm is compared with known classical algorithms using the evaluation function of the peak signal-to-noise ratio. For comparison of the methods we are using parameters such as time, CPU usage, and size of compressed data. The comparison is made on benchmark data in color format YUV. Results of our proposed method are comparable and in some cases better than results of standard classical algorithms.展开更多
基金The National Natural Science Foundation of China(No.60972001,61374194)
文摘To track the vehicles under occlusion, a vehicle tracking algorithm based on blocks is proposed. The target vehicle is divided into several blocks of uniform size, in which the edge block can overlap its neighboring blocks. All the blocks＇ motion vectors are estimated, and the noise motion vectors are detected and adjusted to decrease the error of motion vector estimation. Then, by moving the blocks based on the adjusted motion vectors, the vehicle is tracked. Aiming at the occlusion between vehicles, a Markov random field is established to describe the relationship between the blocks in the blocked regions. The neighborhood of blocks is defined using the Euclidean distance. An energy function is defined based on the blocks＇ histograms and optimized by the simulated annealing algorithm to segment the occlusion region. Experimental results demonstrate that the proposed algorithm can track vehicles under occlusion accurately.
文摘Image sequences processing and video encoding are extremely time consuming problems. The time complexity of them depends on image contents. This paper presents an estimation of a block motion method for video coding with edge alignment. This method uses blocks of size 4 × 4 and its basic idea is to find motion vector using the edge position in each video coding block. The method finds the motion vectors more accurately and faster than any known classical method that calculates all the possibilities. Our presented algorithm is compared with known classical algorithms using the evaluation function of the peak signal-to-noise ratio. For comparison of the methods we are using parameters such as time, CPU usage, and size of compressed data. The comparison is made on benchmark data in color format YUV. Results of our proposed method are comparable and in some cases better than results of standard classical algorithms.
