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This paper presents an online feature selection algorithm
for video object tracking. Using the object and background
pixels from the previous fr a me as training samples, we model the
feature selection problem as finding a good subset of features to
better classify object from background in current fr a me.相关搜索： ONLINE
SELECTION
adaboost
for video object tracking. Using the object and background
pixels from the previous fr a me as training samples, we model the
feature selection problem as finding a good subset of features to
better classify object from background in current fr a me.相关搜索： ONLINE
SELECTION
adaboost
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下载文件列表
| 文件名 | 大小 | 更新时间 |
|---|---|---|
| 2.pdf | 554634 | 2017-04-24 |