Real time human tracking using improved CAM-shift
Ngoc-Quan Nguyen, Shun‐Feng Su, Quoc‐Viet Tran, Van‐Truong Nguyen, Jin-Tsong Jeng · 2017
In this paper, a novel approach is introduced for tracking human targets in cases of high influence from complexity of environment. In real world applications, the need of interaction in real time between a tracking system and human plays an important role. In the proposed approach, a RGB-D camera is utilized to acquire the depth information which is considered to define the Depth Of Interest (DOI). This DOI is used to combine with the CAM-shift algorithm in human tracking. The Kalman filter is also implemented to help in predicting the direction of target. Comparing with the original CAM-shift algorithm, our approach performs more accurate and more effective results. The experiment results also show that our system can be implemented for real-time applications as well.