People-tracking-by-detection and people-detection-by-tracking

Both detection and tracking people are challenging problems, especially in complex real world scenes that commonly involve multiple people, complicated occlusions, and cluttered or even moving backgrounds. People detectors have been shown to be able to locate pedestrians even in complex street scenes, but false positives have remained frequent. The identification of particular individuals has remained challenging as well. On the other hand, tracking methods are able to find a particular individual in image sequences, but are severely challenged by real-world scenarios such as crowded street scenes. In this paper, we combine the advantages of both detection and tracking in a single framework. The approximate articulation of each person is detected in every frame based on local features that model the appearance of individual body parts. Prior knowledge on possible articulations and temporal coherency within a walking cycle are modeled using a hierarchical Gaussian process latent variab...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Mykhaylo Andriluka, Stefan Roth, Bernt Schiele
• Keywords: Cluttered Scenes, Complex Street Scenes, Computer Vision, Crowded Street Scenes, CVPR 2008, Latent Variable Model, Real World Scenes