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Face Detection and Pose Estimation using Triplet Invariants / Ansiktsdetektering med hjälp av triplet-invarianter

Face detection and pose estimation are two widely studied problems - mainly because of their use as subcomponents in important applications, e.g. face recognition. In this thesis I investigate a new approach to the general problem of object detection and pose estimation and apply it to faces. Face detection can be considered a special case of this general problem, but is complicated by the fact that faces are non-rigid objects. The basis of the new approach is the use of scale and orientation invariant feature structures - feature triplets - extracted from the image, as well as a biologically inspired associative structure which maps from feature triplets to desired responses (position, pose, etc.). The feature triplets are constructed from curvature features in the image and coded in a way to represent distances between major facial features (eyes, nose and mouth). The final system has been evaluated on different sets of face images.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-1060
Date January 2002
CreatorsIsaksson, Marcus
PublisherLinköpings universitet, Bildbehandling, Linköpings universitet, Tekniska högskolan, Institutionen för systemteknik
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess
RelationLiTH-ISY-Ex ; 3223

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