TY - JOUR PY - 2012// TI - Pedestrian Detection: An Evaluation of the State of the Art JO - IEEE transactions on pattern analysis and machine intelligence A1 - Dollar, Piotr A1 - Wojek, Christian A1 - Schiele, Bernt A1 - Perona, Pietro SP - 743 EP - 761 VL - 34 IS - 4 N2 - Pedestrian detection is a key problem in computer vision, with several applications that have the potential to positively impact quality of life. In recent years, the number of approaches to detecting pedestrians in monocular images has grown steadily. However, multiple datasets and widely varying evaluation protocols are used, making direct comparisons difficult. To address these shortcomings, we perform an extensive evaluation of the state of the art in a unified framework. We make three primary contributions: (1) we put together a large, well-annotated and realistic monocular pedestrian detection dataset and study the statistics of the size, position and occlusion patterns of pedestrians in urban scenes, (2) we propose a refined per-frame evaluation methodology that allows us to carry out probing and informative comparisons, including measuring performance in relation to scale and occlusion, and (3) we evaluate the performance of sixteen pre-trained state-of-the-art detectors across six datasets. Our study allows us to assess the state of the art and provides a framework for gauging future efforts. By determining the key components of successful detectors and common conditions under which existing methods fail, we help identify open problems and future research directions in pedestrian detection.
Language: en
LA - en SN - 0162-8828 UR - http://dx.doi.org/10.1109/TPAMI.2011.155 ID - ref1 ER -