Application of Heuristic Optimization Methods to Video Object Tracking

Autor: Jhan, Young-Shixa, 詹詠翔
Rok vydání: 2018
Druh dokumentu: 學位論文 ; thesis
Popis: 106
Object tracking is a common and essential task in video processing. This study approaches the object tracking problem using heuristic optimization methods. HSV color space is used as features for object matching. We evaluate the performance of particle filter, particle swarm optimization and grey wolf optimizer. Tracking rate, tracking accuracy and tracking time are important criteria in our comparative study. Experimental results reveal that particle swarm optimization prevails in object tracking applications.
Databáze: Networked Digital Library of Theses & Dissertations