Application of tracking-learning-detection for object tracking in stereoscopic images

Abstract

We use Tracking-Learning-Detection algorithm (TLD) [1]-[3] to localize and track objects in images sensed simultaneously by two parallel cameras in order to determine 3D coordinates of the tracked object. TLD method was chosen for its state-of-art performance and high robustness. TLD stores the object to be tracked as a set of 2D grayscale images that is incrementally built. We have implemented the 3D tracking system into a PC, communicating with the Nao humanoid robot [4][5] equipped with a stereo camera head. Experiments evaluating the accuracy of the 3D tracking system are presented. The robot uses feed-forward control to touch the tracked object. The controller is an artificial neural network trained using the error Back- Propagation algorithm. Experiments evaluating the success rate of the robot touching the object are presented.