HDR imaging for enchancing people detection and tracking in indoor environments

Abstract

Videos and image sequences of indoor environments with challenging illumination conditions often capture either brightly lit or dark scenes where every single exposure may contain overexposed and/or underexposed regions. High Dynamic Range (HDR) images contain information that standard dynamic range ones, often mentioned also as low dynamic range images (SDR/LDR) cannot capture. This paper investigates the contribution of HDR imaging in people detection and tracking systems. In order to evaluate this contribution of the HDR imaging in the accuracy and robustness of pedestrian detection and tracking in challenging indoor visual conditions, two state of the art trackers of different complexity were implemented. To this direction data were collected taking into account the requirements and real-life indoor scenarios and HDR frames were produced. The algorithms were applied to the SDR data and their corresponding HDR data and were compared and evaluated for their robustness and accuracy in terms of precision and recall. Results show that that the use of HDR images enhances the performance of the detection and tracking scheme, making it robust and more reliable.