Vision based object follower automated guided vehicle using compressive tracking and stereo-vision

Abstract

Integration of a visual sensing system plays a vital role in automated navigation by providing a sensing ability of the surrounding environment. The problem of object following is challenging due to changes in appearance that can occur due to motion, pose, illumination and occlusion. The real-time implementation of a computer vision based object following system is presented in this paper. The position of the object to be followed is determined by processing a real time image feed from a calibrated stereo-camera. The method incorporates compressive tracking and stereo-vision based disparity mapping boosted with relocation of the tracking window using Speeded Up Robust Features (SURF). The proposed algorithm runs in realtime and performs favorably in terms of computational efficiency, accuracy and robustness.

A robust tracking algorithm for a human‐following mobile robot

“…In recent years, many research works on the human-following system are vision based. Verma et al [12] presented to develop a robust vision-based tracking algorithm using speeded-up robust features (SURF). Pang et al [13] presented a tracker which is using the kernelized correlation filter (KCF) to detect the target in multiple scales.…”

“…Verma et al. [12] presented to develop a robust vision‐based tracking algorithm using speeded‐up robust features (SURF). Pang et al.…”