Title :
Salient region detection using high level feature
Author :
Zhong Liu ; Weihai Chen ; Xingming Wu
Author_Institution :
Sch. of Autom. Sci. & Electr. Eng., BeiHang Univ., Beijing, China
Abstract :
In the last few decades, selective visual attention has been extensively studied for its promising contributions to computer vision applications. Many different models have been proposed to compute visual saliency, which can be coarsely formulated as computational or psychophysical. Most existing methods are based on bottom-up mechanism, an automatic human behavior to guide gaze allocation. And low level features such as color, intensity and orientation are commonly adopted to compute saliency map. In this work, we propose a saliency computation method that integrates high-level information of object with low-level features. The result map is more suitable for most top-down tasks in the field of mobile robot requiring object information.
Keywords :
computer vision; feature extraction; gaze tracking; image colour analysis; automatic human behavior; color feature; computer vision applications; gaze allocation; high-level object information; intensity feature; low-level features; mobile robot; orientation feature; saliency computation method; saliency map; salient region detection; selective visual attention; top-down tasks; visual saliency; Computational modeling; Detectors; Feature extraction; Image color analysis; Image segmentation; Object detection; Visualization; HOG; features; high level cues; saliency; visual attention;
Conference_Titel :
Control Automation Robotics & Vision (ICARCV), 2014 13th International Conference on
DOI :
10.1109/ICARCV.2014.7064488