Accurate Object Segmentation for Video Sequences via Temporal-Spatial-Frequency Saliency Model

作者：Xu, Bing^*; Niu, Yanxiong

来源：IEEE Intelligent Systems, 2018, 33(1): 18-28.

DOI：10.1109/mis.2017.383122910

In practical applications of video object segmentation, a major challenge is how to increase the accuracy and robustness of complex dynamic scenes and achieve positive scalability under camera displacement conditions. This paper proposes a novel approach to object segmentation by combining information in temporal, spatial, and frequency domains to realize complementary superiority. Four components-motion, color, luminance, and spectral residual from three domains-are applied to structure the temporal-spatial-frequency saliency (TSFS) model. A determining rule is defined to merge the components into a final model. The proposed model is evaluated on two representative video-sequence datasets. The experimental results indicate that the model is more accurate, robust, and effective than other state-of-the-art methods, and can satisfy the requirements of segmenting the object in complex dynamic scenes and large camera displacement conditions.

• 出版日期2018-2
• 单位北京航空航天大学