Salient object detection method based on multiple semantic features

Chunyang Wang; Chunyan Yu; Meiping Song; Yulei Wang

doi:10.1117/12.2303355

10 April 2018 Salient object detection method based on multiple semantic features

Chunyang Wang, Chunyan Yu, Meiping Song, Yulei Wang

Proceedings Volume 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017); 106150F (2018) https://doi.org/10.1117/12.2303355
Event: Ninth International Conference on Graphic and Image Processing, 2017, Qingdao, China

Abstract

The existing salient object detection model can only detect the approximate location of salient object, or highlight the background, to resolve the above problem, a salient object detection method was proposed based on image semantic features. First of all, three novel salient features were presented in this paper, including object edge density feature (EF), object semantic feature based on the convex hull (CF) and object lightness contrast feature (LF). Secondly, the multiple salient features were trained with random detection windows. Thirdly, Naive Bayesian model was used for combine these features for salient detection. The results on public datasets showed that our method performed well, the location of salient object can be fixed and the salient object can be accurately detected and marked by the specific window.

Citation Download Citation

Chunyang Wang, Chunyan Yu, Meiping Song, and Yulei Wang "Salient object detection method based on multiple semantic features", Proc. SPIE 10615, Ninth International Conference on Graphic and Image Processing (ICGIP 2017), 106150F (10 April 2018); https://doi.org/10.1117/12.2303355

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