DocumentCode :
253725
Title :
Salient Region Detection via High-Dimensional Color Transform
Author :
Jiwhan Kim ; Dongyoon Han ; Yu-Wing Tai ; Junmo Kim
Author_Institution :
Dept. of Electr. Eng., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea
fYear :
2014
fDate :
23-28 June 2014
Firstpage :
883
Lastpage :
890
Abstract :
In this paper, we introduce a novel technique to automatically detect salient regions of an image via high-dimensional color transform. Our main idea is to represent a saliency map of an image as a linear combination of high-dimensional color space where salient regions and backgrounds can be distinctively separated. This is based on an observation that salient regions often have distinctive colors compared to the background in human perception, but human perception is often complicated and highly nonlinear. By mapping a low dimensional RGB color to a feature vector in a high-dimensional color space, we show that we can linearly separate the salient regions from the background by finding an optimal linear combination of color coefficients in the high-dimensional color space. Our high dimensional color space incorporates multiple color representations including RGB, CIELab, HSV and with gamma corrections to enrich its representative power. Our experimental results on three benchmark datasets show that our technique is effective, and it is computationally efficient in comparison to previous state-of-the-art techniques.
Keywords :
edge detection; image colour analysis; CIELab; HSV; gamma corrections; high-dimensional color transform; human perception; low dimensional RGB color; saliency map; salient region detection; Color; Feature extraction; Histograms; Image color analysis; Transforms; Vectors; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on
Conference_Location :
Columbus, OH
Type :
conf
DOI :
10.1109/CVPR.2014.118
Filename :
6909513
Link To Document :
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