Learn to segment attention object from low DoF image

In this paper, a novel segmentation algorithm is proposed to extract attention object (i.e., focus object) from Low depth of field image. In order to recognize the focus object, we first decompose the image into multiple segments that are described by visual words. Each visual word is computed from a filter bank to represent the high frequency components. The boosting method is then used to generate a strong classifier for each training image. Given a test image, we employ the voting algorithm to achieve the attention decision according to obtained strong classifiers. To extract focus objects from the test image, two-level segmentation method is proposed, which includes region and pixel levels segmentation. Experimental evaluation on test images shows that the proposed method is capable of segmenting the attention object quite effectively.