• Publications
  • Influence
Mining actionlet ensemble for action recognition with depth cameras
TLDR
In this paper, an actionlet ensemble model is learnt to represent each action and to capture the intra-class variance in the actions. Expand
  • 1,255
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Sparse reconstruction cost for abnormal event detection
TLDR
We propose to detect abnormal events via a sparse reconstruction over the normal bases. Expand
  • 596
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Learning Actionlet Ensemble for 3D Human Action Recognition
TLDR
We propose to characterize the human actions with a novel actionlet ensemble model, which represents the interaction of a subset of human joints. Expand
  • 381
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Robust Part-Based Hand Gesture Recognition Using Kinect Sensor
TLDR
We propose a novel distance metric, Finger-Earth Mover's Distance (FEMD), to measure the dissimilarity between hand shapes. Expand
  • 578
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Robust hand gesture recognition based on finger-earth mover's distance with a commodity depth camera
TLDR
We propose a novel distance metric for hand dissimilarity measure, called Finger-Earth Mover's Distance (FEMD). Expand
  • 392
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Fast action proposals for human action detection and search
  • Gang Yu, Junsong Yuan
  • Mathematics, Computer Science
  • IEEE Conference on Computer Vision and Pattern…
  • 7 June 2015
TLDR
In this paper we target at generating generic action proposals in unconstrained videos. Expand
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Abnormal event detection in crowded scenes using sparse representation
TLDR
We propose the sparse reconstruction cost (SRC) over the normal dictionary to measure the normalness of the testing sample. Expand
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Towards Scalable Summarization of Consumer Videos Via Sparse Dictionary Selection
TLDR
The rapid growth of consumer videos requires an effective and efficient content summarization method to provide a user-friendly way to manage and browse the huge amount of video data. Expand
  • 242
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3D Convolutional Neural Networks for Efficient and Robust Hand Pose Estimation from Single Depth Images
TLDR
We propose a simple, yet effective approach for real-time hand pose estimation from single depth images using three-dimensional Convolutional Neural Networks (CNNs). Expand
  • 166
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Robust 3D Hand Pose Estimation in Single Depth Images: From Single-View CNN to Multi-View CNNs
TLDR
We propose a novel 3D regression method using multi-view CNNs that can better exploit depth cues to recover fully 3D information of hand joints without model fitting. Expand
  • 205
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