In this paper, we address the problem of automatically detecting and tracking a variable number of persons in complex
scenes using a monocular, potentially moving, uncalibrated ca...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...
This paper presents a new statistical model for detecting and tracking deformable objects such as pedestrians, where large shape variations induced by local shape deformation can ...
Pedestrian detection is an important problem in computer vision due to its importance for applications such as visual surveillance, robotics, and automotive safety. This paper push...
Abstract. In this paper, we present a fully automatic approach to multiple human detection and tracking in high density crowds in the presence of extreme occlusion. Human detection...
We propose a novel approach for multi-person trackingby-
detection in a particle filtering framework. In addition
to final high-confidence detections, our algorithm uses the
con...
Michael D. Breitenstein, Fabian Reichlin, Bastian ...