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2015 | OriginalPaper | Buchkapitel

Statistical Prior Based Deformable Models for People Detection and Tracking

verfasst von : Amira Soudani, Ezzeddine Zagrouba

Erschienen in: Neural Information Processing

Verlag: Springer International Publishing

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Abstract

This paper presents a new approach to segment and track people in video. The basic idea is the use of deformable model with incorporation of statistical prior. We propose an hybrid energy model that incorporates a global and a statistical based energy terms in order to improve the tracking task even under occlusion conditions. Target models are initialized at the first frame, then predictions are constructed based on motion vectors. Therefore, we apply an hybrid active contour model in order to segment tracked people. Experiments show the ability of the proposed algorithm to detect, segment and track people well.

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Literatur
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Metadaten
Titel
Statistical Prior Based Deformable Models for People Detection and Tracking
verfasst von
Amira Soudani
Ezzeddine Zagrouba
Copyright-Jahr
2015
DOI
https://doi.org/10.1007/978-3-319-26555-1_44