Category classification with ROIs using object detector

Abstract

Visual category recognition is challenging in computer vision and has several problem. Some of problems on visual category recognition are variance to the object instance position and background clutter. In this paper, we propose method select region of interest(ROI) in training and recognizing automatically. This provide invariance to object instance position and removing background clutter. In training phase, we make object detector to select ROI in recognizing automatically. The object detector is made by training regions of object and non-object, which determine a ROI without user annotation by using class label and some same class image of set of training image set. In this paper, the set of experiments is on the image database. We prove our proposed method can achieve high accuracy and recognize object position in training and recognizing