A study on robust object recognition system for intelligent security camera by using alternative deep learning

Abstract

An alternative learning and its application to construct a robust object recognition system for intelligent security camera(RORSIS) is presented in this paper. We show some experimental results of the development of the new robust 3-D object recognition system for intelligent security camera. In this system, a deep neural network and alternative learning using 3-D CG are key techniques for object recognition from a free viewpoint. Alternative learning is effective approach for the machine learning that depends on huge amount of tarining data. Some appearance based characteristics are determined from captured images, and the system uses a deep neural network, called AlexNet, to automatically classify bicycle, automobile and so on. The proposed system shows that several kinds of equipments can be recognized from a free view point. Experimental results show that the system can effectively recognize four kinds of real objects with 99.5% accuracy.