Abstract
Structure information is a hot spot currently in the domain of computer vision. As many people had applied structure information to their method, few people employed degradation information to their algorithm. However the degradation itself contains some important information. In this paper, we introduce a Structured Degradation Model with degradation assessment of the target to solve the tracking problem. To track the target in non-uniform degraded video, autocorrelation is used to generate the direction map and Tenengrad is used to extract the degradation degree of each target part. In our Structured Degradation Model, an undirected graph of the target is generated to track the target. The nodes of the graph are the target parts and the edges are the interactions between the parts. Experimental result shows that our method performs well especially for object tracking in degraded video.
This work was supported by Zhejiang Provincial Natural Science Foundation of China under Grant number LY15F020031 and LQ16F030007, National Natural Science Foundation of China (NSFC) under Grant numbers 11302195 and 61401397.
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Feng, Y., Liu, S., Zhang, S. (2016). Structured Degradation Model for Object Tracking in Non-uniform Degraded Videos. In: Tan, T., Li, X., Chen, X., Zhou, J., Yang, J., Cheng, H. (eds) Pattern Recognition. CCPR 2016. Communications in Computer and Information Science, vol 662. Springer, Singapore. https://doi.org/10.1007/978-981-10-3002-4_29
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DOI: https://doi.org/10.1007/978-981-10-3002-4_29
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