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Visual detection and tracking of unknown number of objects with nonparametric clustering methods

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Topkaya, İbrahim Saygın (2016) Visual detection and tracking of unknown number of objects with nonparametric clustering methods. [Thesis]

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Official URL: http://risc01.sabanciuniv.edu/record=b1630640 (Table of Contents)

Abstract

Clustering methods that do not expect the number of clusters to be known a priori and infer the number of clusters are known as nonparametric clustering methods in the literature. In this thesis we propose novel approaches to common computer vision applications using nonparametric clustering. We attack the problems of multiple object tracking and people counting. Our main motivation is to approach those as data association tasks where we de ne the data association problem speci c to the nature of the application and bene t from the nonparametric nature of the clustering model. We rst propose a detection free tracking method which tracks an unknown number of objects by clustering superpixels. We de ne the clusters as targets with spatial and visual features and track their changes through time by sequential clustering. The clusters yield tracked targets through time. We also propose a method for clustering short track segments into unknown number of tracks. The clustering similarity is de ned using the spatio-temporal features of the short track segments. The clustering process yields robust tracks of objects through time. We use this approach also to improve the tracking results of the detection free tracking proposed before. Finally we cluster raw person detector outputs to obtain groups of people in a scene and estimate the number of people inside a cluster using the features already extracted for clustering with a proposed metric which is invariant to perspective distortion.

Item Type:Thesis
Additional Information:Yükseköğretim Kurulu Tez Merkezi Tez No: 434059.
Uncontrolled Keywords:Nonparametric clustering. -- Dirichlet process mixture models. -- Chinese restaurant process. -- Multiple object tracking. -- People counting. -- Parametrik olmayan kümeleme. -- Dirichlet süreç karışım modelleri. -- Çin restoranı süreci. -- Çoklu nesne takibi. -- İnsan sayımı.
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800-8360 Electronics > TK7885-7895 Computer engineering. Computer hardware
ID Code:34850
Deposited By:IC-Cataloging
Deposited On:24 May 2018 15:35
Last Modified:25 Mar 2019 17:28

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