Video tracking is a complex problem because the environment, in which video motion needs to be tracked, is widely varied based on the application and poses several constraints on the design and performance of the trac...Video tracking is a complex problem because the environment, in which video motion needs to be tracked, is widely varied based on the application and poses several constraints on the design and performance of the tracking system. Current datasets that are used to evaluate and compare video motion tracking algorithms use a cumulative performance measure without thoroughly analyzing the effect of these different constraints imposed by the environment. But it needs to analyze these constraints as parameters. The objective of this paper is to identify these parameters and define quantitative measures for these parameters to compare video datasets for motion tracking.展开更多
A new no-reference blocking artifact metric for B-DCT compression video is presented in this paper. We first present a new definition of blocking artifact and a new method for measuring perceptive blocking artifact ba...A new no-reference blocking artifact metric for B-DCT compression video is presented in this paper. We first present a new definition of blocking artifact and a new method for measuring perceptive blocking artifact based on HVS taking into account the luminance masking and activity masking characteristic. Then, we propose a new concept of blocking artifact cluster and the algorithm for clustering blocking artifacts. Considering eye movement and fixation, we select several clusters with most serious blocking artifacts and utilize the average of their blocking artifacts to assess the total blocking artifact of B-DCT reconstructed video. Experimental results illustrating the performance of the proposed method are presented and evaluated.展开更多
文摘Video tracking is a complex problem because the environment, in which video motion needs to be tracked, is widely varied based on the application and poses several constraints on the design and performance of the tracking system. Current datasets that are used to evaluate and compare video motion tracking algorithms use a cumulative performance measure without thoroughly analyzing the effect of these different constraints imposed by the environment. But it needs to analyze these constraints as parameters. The objective of this paper is to identify these parameters and define quantitative measures for these parameters to compare video datasets for motion tracking.
基金Project (No. YJCB2003017MU) supported by Huawei Technology Fund, China
文摘A new no-reference blocking artifact metric for B-DCT compression video is presented in this paper. We first present a new definition of blocking artifact and a new method for measuring perceptive blocking artifact based on HVS taking into account the luminance masking and activity masking characteristic. Then, we propose a new concept of blocking artifact cluster and the algorithm for clustering blocking artifacts. Considering eye movement and fixation, we select several clusters with most serious blocking artifacts and utilize the average of their blocking artifacts to assess the total blocking artifact of B-DCT reconstructed video. Experimental results illustrating the performance of the proposed method are presented and evaluated.