Miodrag Dimitrijevic

University of Niš | NIS · Department of Computer Science

We present a novel approach to detecting human silhouettes in monocular sequences that achieves very low rates of both false positives and negatives by combining shape and mo- tion information. To this end, we use sequences of moving silhouettes built using motion capture data that we match against short image sequences. We demonstrate the effectiv...

We combine detection and tracking techniques to achieve robust 3D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on detecting key postures, which can be done reliably, using a motion model to infer 3D poses between consecutive detections, and finally refining them over the whole sequence...

We combine detection and tracking techniques to achieve robust 3-D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on detecting key postures, which can be done reliably, using a motion model to infer 3-D poses between consecutive detections, and finally refining them over the whole sequenc...

We present a template-based approach to detecting human silhouettes in a specific walking pose. Our templates consist of short sequences of 2D silhouettes obtained from motion capture data. This lets us incorporate motion information into them and helps distinguish actual people who move in a predictable way from static objects whose outlines rough...

We propose a face reconstruction technique that produces models that not only look good when texture mapped, but are also metrically accurate. Our method is designed to work with short uncalibrated video or movie sequences, even when the lighting is poor resulting in specularities and shadows that complicate the algorithm's task. Our approach relie...