Visual tracking in video sequences based on biologically inspired mechanisms

Abstract

Visual tracking is the process of locating one or more objects based on their appearance. The high variation in the conditions and states of a moving object and presence of challenges such as background clutter, illumination variation, occlusion, etc. makes this problem extremely complex, and hard to achieve a robust algorithm in this field. However, unlike the machine vision, in the biological vision, the task of visual tracking is ideally conducted even in the worst conditions. Consequently, in this paper, taking into account the superior performance of biological vision in visual tracking, a biologically inspired visual tracking algorithm is introduced. The proposed algorithm inspiring the task-driven recognition procedure of the primary layers of the ventral pathway, and visual cortex mechanisms including spatial–temporal processing, motion perception, attention, and saliency to track a single object in the video sequence. For this purpose, a set of low-level features including the oriented-edges, color, and motion information (inspired by the layer V1) extracted from the target area and based on the discrimination rate that each feature creates with the background (inspired by the saliency mechanism), a subset of these features are employed to generate the appearance model and identify the target location. Moreover, by memorizing the shape and motion information (inspired by the short-term memory) scale variation and occlusion are handled. The experimental results showed that the proposed algorithm can well handle most of the visual tracking challenges, achieve high precision in target locating and act in a real-time manner.