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An Efficient Method for Extracting Key-Frames from 3D Human Joint Locations for Action Recognition

  • Md. Hasanul Kabir
  • Ferdous AhmedEmail author
  • Abdullah-Al-Tariq
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9164)

Abstract

Human Action Recognition is one of the intriguing research area of modern Artificial Intelligence and Computer Vision where different techniques are followed to distinguish various human actions. Accuracy of such methods mainly depend on how a sequence of action frames can be represented by a number of most distinguishable frames, otherwise called key frames. In this paper, we have introduced an efficient method to extract key frames by maximizing accumulation of motion between frames for recognizing human actions using the help of 3D skeletal joint locations. Our feature representation is the combination of histogram of joint 3D (HOJ3D) and static posture feature of 3D skeletal joint locations. Then we used Hidden Markov Model (HMM) for human action recognition from the extracted frame sequence.

Keywords

Discriminative patterns 3D skeletons 3D depth images Key frame extraction Action recognition 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Md. Hasanul Kabir
    • 1
  • Ferdous Ahmed
    • 1
    Email author
  • Abdullah-Al-Tariq
    • 1
  1. 1.Department of Computer Science and EngineeringIslamic University of TechnologyDhakaBangladesh

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