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Título | Robust People Detection and Tracking from an overhead Time-of-Flight Camera |
Tipo de publicación | Conference Paper |
Año de publicación | 2017 |
Autores | Fernandez-Rincon, A, Fuentes, D, Losada-Gutiérrez, C, Marron, M, Luna, CA, Macias-Guarasa, J, Mazo, M |
Idioma de publicación | English |
Conference Name | 12th International Conference on Computer Vision Theory and Applications. |
Volumen | 4 |
Páginas | 556-564 |
Editorial | INSTICC/SCITEPRESS |
Conference Location | Porto, Portugal |
Fecha de publicación | 03/2017 |
Numero ISBN | 978-989-758-225-7 |
Palabras clave | People Detection, Time-of-Flight, ToF Camera, ToF Camera., Tracking |
DOI | 10.5220/0006169905560564 |
Resumen | In this paper we describe a system for robust detection of people in a scene, by using an overhead Time of Flight (ToF) camera. The proposal addresses the problem of robust detection of people, by three means: a carefully designed algorithm to select regions of interest as candidates to belong to people; the generation of a robust feature vector that efficiently model the human upper body; and a people classification stage, to allow robust discrimination of people and other objects in the scene. The proposal also includes a particle filter tracker to allow people identification and tracking. Two classifiers are evaluated, based on Principal Component Analysis (PCA), and Support Vector Machines (SVM). The evaluation is carried out on a subset of a carefully designed dataset with a broad variety of conditions, providing results comparing the PCA and SVM approaches, and also the performance impact of the tracker, with satisfactory results. |
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robustpeopledetectionandtrackingfromanoverhead-visapp-2017.pdf | 960.53 KB |