Bagging in Computer Vision

Previous research has shown that aggregated predictors improve the performance of non-parametric function approximation techniques. This paper presents the results of applying aggregated predictors to a computer vision problem, and shows that the method of bagging signi cantly improves performance. In fact, the results are better than those previously reported on other domains. This paper explains this performance in terms of the variance and bias.

• Type: Conference
• Year: 1998
• Where: CVPR
• Authors: Bruce A. Draper, Kyungim Baek
• Keywords: Computer Vision, CVPR 1998, Non-parametric Function Approximation