Open AccessProceedings Article
Multiple-Instance Pruning For Learning Efficient Cascade Detectors
Cha Zhang,Paul A. Viola +1 more
- 03 Dec 2007
- Vol. 20, pp 1681-1688
TL;DR: The multiple instance pruning (MIP) algorithm for soft cascades is proposed, which computes a set of thresholds which aggressively terminate computation with no reduction in detection rate or increase in false positive rate on the training dataset.
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Abstract: Cascade detectors have been shown to operate extremely rapidly, with high accuracy, and have important applications such as face detection Driven by this success, cascade learning has been an area of active research in recent years Nevertheless, there are still challenging technical problems during the training process of cascade detectors In particular, determining the optimal target detection rate for each stage of the cascade remains an unsolved issue In this paper, we propose the multiple instance pruning (MIP) algorithm for soft cascades This algorithm computes a set of thresholds which aggressively terminate computation with no reduction in detection rate or increase in false positive rate on the training dataset The algorithm is based on two key insights: i) examples that are destined to be rejected by the complete classifier can be safely pruned early; ii) face detection is a multiple instance learning problem The MIP process is fully automatic and requires no assumptions of probability distributions, statistical independence, or ad hoc intermediate rejection targets Experimental results on the MIT+CMU dataset demonstrate significant performance advantages
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Paul A. Viola,Michael Jones +1 more
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Robust real-time face detection
Paul A. Viola,Michael Jones +1 more
- 07 Jul 2001
TL;DR: A new image representation called the “Integral Image” is introduced which allows the features used by the detector to be computed very quickly and a method for combining classifiers in a “cascade” which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions.
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