Multi Object Tracking Based on Detection with Deep Learning and Hierarchical Clustering

Multi object tracking is one of the hotspots of computer vision research. Tracking-by-detection is a common approach to multi-object tracking. With the development of machine learning, especially of deep leaning method, the basis for a tracker becomes much more reliable. The method proposed in this paper is based on detection with convolutional neural network and tracking with hierarchical clustering. Experimental evaluation shows that the proposed method achieves overall competitive performance at high frame rates.