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Erschienen in:
2010 | OriginalPaper | Buchkapitel
Multi-view Multi-object Detection and Tracking
verfasst von : Murtaza Taj, Andrea Cavallaro
Erschienen in: Computer Vision
Verlag: Springer Berlin Heidelberg
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Multi-viewtrackers combine data fromdifferent camera views to estimate the temporal evolution of objects across a monitored area. Data to be combined can be represented by object features (such as position, color and silhouette) or by object trajectories in each view. In this Chapter, we classify and survey state-of-the art multi-view tracking algorithms and discuss their applications and algorithmic limitations. Moreover, we present a multi-view track-before-detect approach that consistently detects and recognizes multiple simultaneous objects in a common view, based on motion models. This approach estimates the temporal evolution of objects from noisy data, given their motion model, without an explicit object detection stage.