Rebound of Region of Interest (RROI), a New Kernel-Based Algorithm for Video Object Tracking Applications

• 作者: Andres Alarcon Ramirez Mohamed Chouikha
• 来源期刊: 信号与信息处理(英文)
• 学科: 工学
• 关键词: Video OBJECT TRACKING Cluttered Conditions Kernel-Based Algorithm
• 年，卷（期）: 2014,（4）
• 页码范围: 97-103
• 页数: 7页
• 分类号: TP39

摘要

This paper presents a new kernel-based algorithm for video object tracking called rebound of region of interest (RROI). The novel algorithm uses a rectangle-shaped section as region of interest (ROI) to represent and track specific objects in videos. The proposed algorithm is constituted by two stages. The first stage seeks to determine the direction of the object’s motion by analyzing the changing regions around the object being tracked between two consecutive frames. Once the direction of the object’s motion has been predicted, it is initialized an iterative process that seeks to minimize a function of dissimilarity in order to find the location of the object being tracked in the next frame. The main advantage of the proposed algorithm is that, unlike existing kernel-based methods, it is immune to highly cluttered conditions. The results obtained by the proposed algorithm show that the tracking process was successfully carried out for a set of color videos with different challenging conditions such as occlusion, illumination changes, cluttered conditions, and object scale changes.