Yuta Nakano and Tomoharu Nagao

Recently, we often deal with multi-dimensional data in the field of image processing. Thanks to the evelopment of imaging equipments and computational processing speed, we can process 3D image data. For instance, 3D volume image and video image data have been used in various fields. In general, it is difficult to construct 3D image processing compared with 2D ones. Thus, we previously proposed the method named “3D-ACTIT; Three Dimensional Automatic Construction of Tree-structural Image Transformation” to construct various 3D image processing procedures automatically. This system constructs tree-structural image  rocessing filter from combination of one-input one-output filters and two-inputs one-output filters by using Genetic Programming  (GP) . We give only some training image sets, this system constructs complex 3D image processing  utomatically. By using this system, we succeeded to construct the complex 3D medical image processing. For instance, the extraction processing of internal organs from 3DPET data and abnormal signals from 3D Diffusion Weighted Image are constructed. In addition to the field of medical image processing, in Intelligent Transport system (ITS) and security system, video image processing requires complex and 3D processing. In this paper, we apply 3D-ACTIT to video image data. We took the video image data using some compact robots on the assumption of in-vehicle camera. 3D-ACTIT constructs the processing which extracts the moving objects

Image and Vision Computing 26 (2008) 776–787

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Object recognition is one of the most important tasks of the visual cortex. Even though it has been closely studied in the field of computer vision and neuroscience, the underlying processes in the visual cortex are not completely understood. A model that lately has gained attention is the HMAX model, which describes a feedforward hierarchical structure. This model shows a degree of scale and translation invariance. Our work explores and compares the HMAX model with a simpler model for object recognition emulating simple cells in the primary visual cortex, V1. This model shows a better performance than the HMAX model for translation and scale invariance experiments when an attentional mechanism is employed in realistic conditions. 2007 Elsevier B.V. All rights reserved

Keywords

Object recognition; HMAX; Foveation; Attention; Active vision; Visual cortex; Translation invariance; Scale invariance