Computer Science ›› 2015, Vol. 42 ›› Issue (9): 303-308.doi: 10.11896/j.issn.1002-137X.2015.09.060

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Objectness Proposal Based on Prior Distribution of Geometric Characteristics of Object Regions

LIU Zhi-bin and ZHAO Qi-yang   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Objectness proposal is an emerging problem aiming to improve the efficiency of object detection by reducing candidate windows.The problem was analyzed from the perspective of combinatorial geometric ,and a method was proposed to construct full cover sets which cover all possible object rectangles with a rather small amount of windows.For images no larger than 512×512,supposing all object rectangles are not smaller than 16×16,nearly 19000 windows are sufficient to make up a full cover set.By exploiting the prior distribution of locations/sizes of object rectangles,this amount can be reduced further in a greedy mode.In order to address the diversity of low-probability samples of different image sets,a hybrid scheme mixing the greedy and random methods which has good generality was presented.The new scheme recalls 94.52% object rectangles with 1000 proposal windows,and its DRs on the first ten hot proposal windows are 13.99%~40.29% higher than existing methods in average.

Key words: Object detection,Objectness proposal,Geometric characteristics,Full cover set,Hybrid scheme

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