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» Using a Non-prior Training Active Feature Model
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ICPR
2010
IEEE
13 years 10 months ago
Motif Discovery and Feature Selection for CRF-Based Activity Recognition
Abstract—Due to their ability to model sequential data without making unnecessary independence assumptions, conditional random fields (CRFs) have become an increasingly popular ...
Liyue Zhao, Xi Wang, Gita Sukthankar
TMI
2002
155views more  TMI 2002»
13 years 4 months ago
Active Shape Model Segmentation with Optimal Features
Abstract--An active shape model segmentation scheme is presented that is steered by optimal local features, contrary to normalized first order derivative profiles, as in the origin...
Bram van Ginneken, Alejandro F. Frangi, Joes Staal...
AVBPA
2005
Springer
279views Biometrics» more  AVBPA 2005»
13 years 10 months ago
Active Shape Models with Invariant Optimal Features (IOF-ASMs)
Abstract. This paper is framed in the field of statistical face analysis. In particular, the problem of accurate segmentation of prominent features of the face in frontal view ima...
Federico Sukno, Sebastián Ordas, Constantin...
FGR
2006
IEEE
147views Biometrics» more  FGR 2006»
13 years 8 months ago
Cascaded Classification of Gender and Facial Expression using Active Appearance Models
This paper presents an approach to recognising the gender and expression of face images by means of Active Appearance Models (AAM). Features extracted by a trained AAM are used to...
Yunus Saatci, Christopher Town
AAAI
2008
13 years 7 months ago
Feature Selection for Activity Recognition in Multi-Robot Domains
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that ar...
Douglas L. Vail, Manuela M. Veloso