Motion saliency detection using a temporal fourier transform

被引:19
作者
Chen, Zhe [1 ,2 ]
Wang, Xin [1 ]
Sun, Zhen [1 ]
Wang, Zhijian [1 ]
机构
[1] Hohai Univ, Coll Comp & Informat Engn, Nanjing, Jiangsu, Peoples R China
[2] Nanjing Xiaozhuang Univ, Key Lab Trusted Cloud Comp & Big Data Anal, Nanjing, Peoples R China
基金
中国国家自然科学基金;
关键词
Motion saliency; Temporal Fourier Transform; Moving object detection; ATTENTION; MODEL;
D O I
10.1016/j.optlastec.2015.12.013
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Motion saliency detection aims at detecting the dynamic semantic regions in a video sequence. It is very important for many vision tasks. This paper proposes a new type of motion saliency detection method, Temporal Fourier Transform, for fast motion saliency detection. Different from conventional motion saliency detection methods that use complex mathematical models or features, variations in the phase spectrum of consecutive frames are identified and extracted as the key to obtaining the location of salient motion. As all the calculation is made on the temporal frequency spectrum, our model is independent of features, background models, or other forms of prior knowledge about scenes. The benefits of the proposed approach are evaluated for various videos where the number of moving objects, illumination, and background are all different. Compared with some the state of the art methods, our method achieves both good accuracy and fast computation. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1 / 15
页数:15
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