Experimental Assessment of Probabilistic Integrated Object Recognition and Tracking Methods

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Conference object , Article 01 Jan 2009 Spain English Publisher:Springer Berlin Heidelberg

Authors: Serratosa Casanelles, Francesc; Amézquita Gómez, Nicolás; Alquézar Mancho, René;

doi: 10.1007/978-3-642-10268-4_96

handle: 2117/9245 , 10261/30137

Experimental Assessment of Probabilistic Integrated Object Recognition and Tracking Methods

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Abstract

This paper presents a comparison of two classifiers that are used as a first step within a probabilistic object recognition and tracking framework called PIORT. This first step is a static recognition module that provides class probabilities for each pixel of the image from a set of local features. One of the implemented classifiers is a Bayesian method based on maximum likelihood and the other one is based on a neural network. The experimental results show that, on one hand, both classifiers (although they are very different approaches) yield a similar performance when they are integrated within the tracking framework. And on the other hand, our object recognition and tracking framework obtains good results when compared to other published tracking methods in video sequences taken with a moving camera and including total and partial occlusions of the tracked object.

Country

Spain

Related Organizations

Institute of Robotics and Industrial Informatics
Spain
Universitat Polite`cnica de Catalunya
Spain
Universitat Politècnica de Catalunya
Spain
Universitat Rovira i Virgili
Spain
Spanish National Research Council
Spain

Keywords

Occlusion, Object tracking Object recognition Occlusion Performance evaluation, Visió per ordinador, :Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes [Àrees temàtiques de la UPC], Pattern recognition systems, Object recognition, Object tracking, Classificació INSPEC::Pattern recognition::Object detection, Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo, :Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo [Àrees temàtiques de la UPC], :Pattern recognition [Classificació INSPEC], Classificació INSPEC::Pattern recognition::Computer vision, Performance evaluation, Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Reconeixement de formes, Computer vision, Reconeixement de formes (Informàtica), Classificació INSPEC::Pattern recognition, :Pattern recognition::Computer vision [Classificació INSPEC], :Pattern recognition::Object detection [Classificació INSPEC]

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