Accede a información sobre la estructura de la actividad investigadora de Geintra.
|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-Jimenez, D, Losada, C, Marron-Romera, M, Luna, CA, Macias-Guarasa, J, Mazo, M|
|Idioma de publicación||English|
|Conference Name||12th International Conference on Computer Vision Theory and Applications.|
|Conference Location||Porto, Portugal|
|Fecha de publicación||03/2017|
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.