Non-Planar Infrared-Visible Registration for Uncalibrated Stereo Pairs

Dinh-Luan Nguyen, Pierre-Luc St-Charles, Guillaume-Alexandre Bilodeau; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2016, pp. 63-71

Thermal infrared-visible video registration for non-planar scenes is a new area in visual surveillance. It allows the combination of information from two spectra for better human detection and segmentation. In this paper, we present a novel online framework for visible and thermal infrared registration in non-planar scenes that includes foreground segmentation, feature matching, rectification and disparity calculation. Our proposed approach is based on sparse correspondences of contour points. The key ideas of the proposed framework are the removal of spurious regions at the beginning of videos and a registration methodology for non-planar scenes. Besides, a new non-planar dataset with an associated evaluation protocol is also proposed as a standard assessment. We evaluate our method on both public planar and non-planar datasets. Experimental results reveal that the proposed method can not only successfully handle non-planar scenes but also gets state-of-the-art results on planar ones.