Application of Heuristic Optimization Methods to Video Object Tracking
碩士 === 國立高雄應用科技大學 === 電子工程系碩士班 === 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 filt...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2018
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| Online Access: | http://ndltd.ncl.edu.tw/handle/jnma25 |
| Summary: | 碩士 === 國立高雄應用科技大學 === 電子工程系碩士班 === 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.
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