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ICPR
2008
IEEE
16 years 28 days ago
3D Shape Context and Distance Transform for action recognition
We propose the use of 3D (2D+time) Shape Context to recognize the spatial and temporal details inherent in human actions. We represent an action in a video sequence by a 3D point ...
Franziska Meier, Irfan A. Essa, Matthias Grundmann
CIARP
2006
Springer
15 years 3 months ago
A Method for Detection and Modeling of the Human Spine Based on Principal Curvatures
The detection and modeling of the human spine from scanned 3D data is an important issue in biomedical shape analysis. It can be useful for avoiding invasive treatments like radiog...
Y. Santiesteban, J. M. Sanchiz, José Mart&i...

Publication
200views
13 years 7 months ago
Learning Tags from Unsegmented Videos of Multiple Human Actions
Providing methods to support semantic interaction with growing volumes of video data is an increasingly important challenge for data mining. To this end, there has been some succes...
Timothy Hospedales, Shaogang Gong, Tao Xiang
KI
2007
Springer
15 years 5 months ago
Location-Based Activity Recognition
Learning patterns of human behavior from sensor data is extremely important for high-level activity inference. We show how to extract and label a person’s activities and signiď¬...
Dieter Fox
FGR
1996
IEEE
186views Biometrics» more  FGR 1996»
15 years 3 months ago
Cardboard People: A Parameterized Model of Articulated Image Motion
We extend the work of Black and Yacoob on the tracking and recognition of human facial expressions using parameterized models of optical flow to deal with the articulatedmotion of...
Shanon X. Ju, Michael J. Black, Yaser Yacoob