Analysis of object description methods in a video object tracking environment

• Type: Article in International Scientific Journal
• Date: 2013

Authors

Pedro Carvalho (Author) FEUP; Telmo Oliveira (Author) Other; Lucian Ciobanu (Author) Other; Filipe Gaspar (Author) Other; Luis F Teixeira (Author) FEUP; Rafael Bastos (Author) Other; Jaime S Cardoso (Author) FEUP; Miguel S Dias (Author) Other; Luis Corte Real (Author) FEUP

Journal

Title: Machine Vision and Applications

Vol. 24 No. 6

Pages: 1149-1165

ISSN: 0932-8092

Publisher: Springer Nature

Indexing

ISI Web of Knowledge - 2 Citations

ISI Web of Science

Scopus - 8 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-006-8YH

DOI: 10.1007/s00138-013-0523-z

Abstract (EN): A key issue in video object tracking is the representation of the objects and how effectively it discriminates between different objects. Several techniques have been proposed, but without a generally accepted method. While analysis and comparisons of these individual methods have been presented in the literature, their evaluation as part of a global solution has been overlooked. The appearance model for the objects is a component of a video object tracking framework, depending on previous processing stages and affecting those that succeed it. As a result, these interdependencies should be taken into account when analysing the performance of the object description techniques. We propose an integrated analysis of object descriptors and appearance models through their comparison in a common object tracking solution. The goal is to contribute to a better understanding of object description methods and their impact on the tracking process. Our contributions are threefold: propose a novel descriptor evaluation and characterisation paradigm; perform the first integrated analysis of state-of-the-art description methods in a scenario of people tracking; put forward some ideas for appearance models to use in this context. This work provides foundations for future tests and the proposed assessment approach contributes to the informed selection of techniques more adequately for a given tracking application context.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 17