Human detection based on weighted template matching

Duc Thanh Nguyen, Philip Ogunbona, Wanqing Li

Abstract: This paper proposes a new two-stage human detection method involving matching and verification. A Bayesian framework is developed to verify the matching score obtained from a weighted distance measure. Performance evaluation indicates that the proposed method is able to utilize the flexible matching scheme and produce superior true positive, true negative and low misclassification rates.