BACK-PROPAGATION IMAGE VISUAL SIGNIFICANCE DETECTION METHOD BASED ON DEPTH MAP MINING

摘要

A back-propagation significance detection method based on depth map mining, comprising: for an input image I_o, at a preprocessing phase, obtaining a depth image I_d and an image C_b with four background corners removed of the image I_o; at a first processing phase, carrying out positioning detection on a significant region of the image by means of the obtained image C_b with four background corners removed and the obtained depth image I_d to obtain the preliminary detection result S₁ of a significant object in the image; then carrying out depth mining on a plurality of processing phases of the depth image I_d to obtain corresponding significance detection results; and then optimizing the significance detection result mined in each processing phase by means of a back-propagation mechanism to obtain a final significance detection result map. The method can improve the detection accuracy of the significance object.