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» Self-Supervised Learning for Visual Tracking and Recognition...
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ICMCS
2005
IEEE
113views Multimedia» more  ICMCS 2005»
13 years 10 months ago
HMM-Based Deception Recognition from Visual Cues
Behavioral indicators of deception and behavioral state are extremely difficult for humans to analyze. This research effort attempts to leverage automated systems to augment human...
Gabriel Tsechpenakis, Dimitris N. Metaxas, Mark Ad...
ICRA
2005
IEEE
142views Robotics» more  ICRA 2005»
13 years 10 months ago
A Real-Time Haptic/Graphic Demonstration of how Error Augmentation can Enhance Learning
– We developed a real-time controller for a 2 degree-of-freedom robotic system using xPC Target. This system was used to investigate how different methods of performance error fe...
Yejun Wei, James L. Patton, Preeti Bajaj, Robert S...
ICCV
2005
IEEE
13 years 10 months ago
3D Human Action Recognition Using Spatio-temporal Motion Templates
Our goal is automatic recognition of basic human actions, such as stand, sit and wave hands, to aid in natural communication between a human and a computer. Human actions are infer...
Fengjun Lv, Ramakant Nevatia, Mun Wai Lee
ECCV
2008
Springer
14 years 6 months ago
Simultaneous Visual Recognition of Manipulation Actions and Manipulated Objects
Abstract. The visual analysis of human manipulation actions is of interest for e.g. human-robot interaction applications where a robot learns how to perform a task by watching a hu...
Danica Kragic, David Martínez Mercado, Hedv...
ECCV
2006
Springer
13 years 6 months ago
Recognition and Segmentation of 3-D Human Action Using HMM and Multi-class AdaBoost
Our goal is to automatically segment and recognize basic human actions, such as stand, walk and wave hands, from a sequence of joint positions or pose angles. Such recognition is d...
Fengjun Lv, Ramakant Nevatia