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PR
2008
124views more  PR 2008»
13 years 9 months ago
A daily behavior enabled hidden Markov model for human behavior understanding
This paper presents a Hierarchical Context Hidden Markov Model (HC-HMM) for behavior understanding from video streams in a nursing center. The proposed HC-HMM infers elderly behav...
Pau-Choo Chung, Chin-De Liu
AR
2007
204views more  AR 2007»
13 years 10 months ago
Action recognition and understanding through motor primitives
In robotics, recognition of human activity has been used extensively for robot task learning through imitation and demonstration. However, there has not been much work on modeling...
Isabel Serrano Vicente, Ville Kyrki, Danica Kragic...
ICASSP
2008
IEEE
14 years 4 months ago
Learning with noisy supervision for Spoken Language Understanding
Data-driven Spoken Language Understanding (SLU) systems need semantically annotated data which are expensive, time consuming and prone to human errors. Active learning has been su...
Christian Raymond, G. Riccardfi
COGSCI
2004
62views more  COGSCI 2004»
13 years 9 months ago
Using movement and intentions to understand simple events
In order to understand ongoing activity, observers segment it into meaningful temporal parts. Segmentation can be based on bottom-up processing of distinctive sensory characterist...
Jeffrey M. Zacks
TITS
2010
286views Education» more  TITS 2010»
13 years 4 months ago
Understanding Transit Scenes: A Survey on Human Behavior-Recognition Algorithms
Visual surveillance is an active research topic in image processing. Transit systems are actively seeking new or improved ways to use technology to deter and respond to accidents, ...
Joshua Candamo, Matthew Shreve, Dmitry B. Goldgof,...