A novel biologically inspired computational framework for visual tracking task

چکیده مقاله

Visual tracking is a process in which the location of one or several objects is estimated in a video sequence based on their appearance. High diversity of states and conditions of a moving stimulus and the existence of abundant challenges such as a cluttered background, variations in the objects appearance, and occlusion make this problem very complicated. Although a wide range of diverse algorithms have been introduced in this field, even the state-of-art ones have not been able to achieve high accuracy in facing different challenges of this problem. Nevertheless, by observing the biological world and paying attention to the living beings, particularly humans, it is revealed that the biological visual system performs the visual tracking task ideally. Therefore, inspiring from this biological system and especially its spatiotemporal processing, motion perception, attention, and saliency mechanism, in this paper a new biologically inspired visual tracking framework is proposed. The suggested framework includes a six-phase process in which the executive blocks, their connections, and information flow among them are inspired by the visual cortex. Using visual features extracted in primary layers of the visual cortex as well as the local-global and sparse representation of the object of interest make possible to employ the proposed framework in different conditions. In this paper, the theory of the suggested framework and its biological background is explained. Investigating the procedure of proposed framework from the viewpoint of employed features, spatiotemporal process, and the quiddity of local-global processing indicated that this framework enjoys the ability to manage most of the mentioned challenges, and can robustly track the object of interest in real conditions and application. This paper seeks to bridge biological and machine visions in order to bring the robustness, speed, and accuracy of biological vision into the artificial intelligence world.