Training a multi-exit cascade with linear asymmetric classification for efficient object detection
Efficient visual object detection is of central interest in computer vision and pattern recognition due to its wide ranges of applications. Viola and Jones'detector has become a de facto framework . In this work, we propose a new method to design a cascade of boosted classifiers for fast object detection, which combines linear asymmetric classification (LAC) into the recent multi-exit cascade structure. Therefore, the proposed method takes advantages of both LAC and the multi-exit cascade....[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of IEEE International Conference on Image Processing 2010|
|01_Wang_Training_a_multi-exit_cascade_2010.pdf||441.2 kB||Adobe PDF||Request a copy|
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