Multiple objects tracking technique based on orthogonal variant moments features and K-means clustering
碩士 === 國立屏東教育大學 === 資訊科學系碩士班 === 101 === Traditional Moment although could be tracking objects, not only could not directly tracking multiple objects, but also it’s susceptible to noise interference. In this study, we use Orthogonal Variant Moments features to solve this problem. The first step we u...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2013
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| Online Access: | http://ndltd.ncl.edu.tw/handle/52121726442420030955 |