A modified Mahalanobis distance for human detection in out-door environments

Publication Type:
Conference Proceeding
Proceedings - 2008 the 1st IEEE International Conference on Ubi-Media Computing and Workshops, U-Media2008, 2008, pp. 243 - 248
Issue Date:
Full metadata record
This paper proposes a novel method for human detection from static images based on pixel structure of input images. Each image is divided into four parts, and a weight is assigned to each part of the image. In training stage, all sample images including human images and non-human images are used to construct a Mahalanobis distance map through statistically analyzing the difference between the different blocks on each original image. A projection matrix will be created with Linear Discriminant Method (LDM) based on the Mahalanobis distance map. This projection matrix will be used to transform multidimensional feature vectors into one dimensional feature domain according to a pre-calculated threshold to distinguish human figures from non-human figures. In comparison with the method without introducing weights, the proposed method performs much better. Encouraging experimental results have been obtained based on MIT dataset and our own dataset. © 2008 IEEE.
Please use this identifier to cite or link to this item: