A Multi-Level Visual Tracking Algorithm for Autonomous Vehicles

Abstract

A multi-level visual tracking algorithm is proposed for autonomous vehicles based on mean-shift algorithm, cam-shift algorithm and extended kalman filter estimator. The proposed multi-level visual tracking algorithm is implemented and included in simulation to check its performance. Simulation results are captured after applying existing algorithms, proposed multi-level visual tracking algorithm and observed their performance. The simulated results show that the proposed multi-level visual tracking algorithm identifies and tracks the ground moving target efficiently.

Design and development of an on-board autonomous visual tracking system for unmanned aerial vehicles

“…The main drawbacks of the existing methodology are: -the radar weight constraint, since it is not feasible to put a radar in a UAV; -the high cost of the radar for surveillance and GMT tracking; -longer time required for the operator to perform the operations and requirements; -on-ground image tracking software controlled by the GCS; -difficulties in detecting when a GMT moves out of the frame or is not visible due to occlusions. To overcome the drawbacks listed above, an efficient multi-level autonomous visual tracking algorithm (Kemsaram et al 2017) is included in an on-board AVTS for GMT tracking.…”

“…The on-board multi-level autonomous visual tracking algorithm (Kemsaram et al 2017) is based on the meanshift, cam-shift, and the EKF. It estimates the GMT path and computes the pixel position of the GMT centroid in the image.…”

“…Manual visual tracking software requires a lot of time for the communication between the operator and the SUAV. Hence, an on-board AVTS, which would receive the video frames from the on-board SUAV camera and would contain an efficient multi-level autonomous visual tracking algorithm based on image processing (Kemsaram et al 2017), is needed to guide the SUAV and to control the camera for tracking the GMT continuously. The main objective is to design and develop an efficient on-board AVTS for SUAVs.…”