Leveraging hierarchical parametric networks for skeletal joints based action segmentation and recognition

Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition

Volumn , Issue , 2014, Pages 724-731

  Wu, Di ^a   Shao, Ling ^a  

^a UNIVERSITY OF SHEFFIELD   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BIOMIMETICS; DEEP NEURAL NETWORKS; HIDDEN MARKOV MODELS; MULTILAYER NEURAL NETWORKS; MUSCULOSKELETAL SYSTEM; OBJECT RECOGNITION; TRELLIS CODES;

ACTION RECOGNITION; ACTION SEGMENTATION; DYNAMIC FRAMEWORK; EMISSION DISTRIBUTION; EMISSION PROBABILITIES; GAUSSIAN MIXTURE MODEL; PARAMETRIC NETWORK; SHAPE CONTEXT FEATURES;

PROBABILITY DISTRIBUTIONS;

EID: 84911438024     PISSN: 10636919     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2014.98     Document Type: Conference Paper

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