3D Object recognition based on some aspects of the infant vision system and associative memory

A view-based method for 3D object recognition based on some biological aspects of infant vision is proposed in this paper. The biological hypotheses of this method are based on the role of the response to low frequencies at early stages as well as some conjectures concerning how an infant detects subtle features (stimulating points) from an object. In order to recognize an object from different images of it (at different orientations from 0° to 360°), we make use of a dynamic associative memory (DAM). As the infant vision responds to low frequencies of the signal, a low-filter is first used to remove high frequency components from the image. Then, we detect subtle features in the image by means of a random feature selection detector. At last, the DAM is fed with this information for training and recognition. To test the accuracy of the proposed model, we use the Columbia Object Image Library (COIL 100) database.