Filling The Gap in Quality Assessment of Video Object Tracking Luís Corte Real en Pedro Miguel Carvalho en Jaime Cardoso en 2017-11-17T11:56:09Z 2017-11-17T11:56:09Z 2012 en
dc.description.abstract Current evaluation methods either rely heavily on reference information manually annotated or, by completely avoiding human input, provide only a rough evaluation of the performance of video object tracking algorithms. The main objective of this paper is to present a novel approach to the problem of evaluating video object tracking algorithms. It is proposed to use different types of reference information and the combination of heterogeneous metrics for the purpose of approximating the ideal error. This will enable a significant decrease of the required reference information, thus bridging the gap between metrics with different requirements concerning this type of data. As a result, evaluation frameworks can aggregate the benefits from individual approaches while overcoming their weaknesses, providing a flexible and powerful tool to assess and characterize the behavior of the tracking algorithms. en
dc.language eng en
dc.relation 4358 en
dc.relation 243 en
dc.relation 3889 en
dc.rights info:eu-repo/semantics/openAccess en
dc.title Filling The Gap in Quality Assessment of Video Object Tracking en
dc.type article en
dc.type Publication en