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Accurate Object Localization with Shape Masks
Abstract : This paper proposes an object class localization approach which goes beyond bounding boxes, as it also determines the outline of the object. Unlike most current localization methods, our approach does not require any hypothesis parameter space to be defined. Instead, it directly generates, evaluates and clusters shape masks. Thus, the presented framework produces much richer answers to the object class localization problem. For example, it easily learns and detects possible object viewpoints and articulations, which are often well characterized by the object outline. We evaluate the proposed approach on the challenging natural-scene Graz-02 object classes dataset. The results demonstrate the extended localization capabilities of our method.
Keywords :
computer vision
object recognition
https://hal.inria.fr/inria-00548679
Contributor : Thoth Team <>
Submitted on : Monday, December 20, 2010 - 10:28:09 AM
Last modification on : Tuesday, February 9, 2021 - 3:16:02 PM
Long-term archiving on: : Monday, March 21, 2011 - 3:31:20 AM
Contributor : Thoth Team <>
Submitted on : Monday, December 20, 2010 - 10:28:09 AM
Last modification on : Tuesday, February 9, 2021 - 3:16:02 PM
Long-term archiving on: : Monday, March 21, 2011 - 3:31:20 AM