Efficient Human Motion Retrieval via Temporal Adjacent Bag of Words and Discriminative Neighborhood Preserving Dictionary Learning

Xin Liu*, Gao Feng He, Shu Juan Peng, Yiu Ming CHEUNG, Yuan Yan Tang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

Human motion retrieval from motion capture data forms the fundamental basis for computer animation. In this paper, the authors propose an efficient human motion retrieval approach via temporal adjacent bag of words (TA-BoW) and discriminative neighborhood preserving dictionary learning (DNP-DL). The retrieval process includes two phases: offline training and online retrieval. In the first phase, the original skeleton model is first simplified and then pairwise joint distances are computed to characterize each motion frame. Then, a novel motion descriptor, namely TA-BoW, is proposed to discriminatively code the motion appearances, through which the articulated complexity and spatiotemporal dimensionality can be greatly reduced. Subsequently, by considering the neighborhood relationships of intraclass structure and the advantage of Fisher criterion, a DNP-DL method is exploited through which each human action can be discriminatively and sparsely represented by a linear combination of such dictionary atoms. In the second phase, a hierarchical retrieval mechanism is used by incorporating the sparse classification and chi-square ranking, whereby the searching range is significantly reduced. The experimental results show that the proposed human motion retrieval approach performs better than the state-of-the-art competing approaches.

Original languageEnglish
Article number7885610
Pages (from-to)763-776
Number of pages14
JournalIEEE Transactions on Human-Machine Systems
Volume47
Issue number6
DOIs
Publication statusPublished - Dec 2017

Scopus Subject Areas

  • Human Factors and Ergonomics
  • Control and Systems Engineering
  • Signal Processing
  • Human-Computer Interaction
  • Computer Science Applications
  • Computer Networks and Communications
  • Artificial Intelligence

User-Defined Keywords

  • Hierarchical retrieval mechanism
  • human motion retrieval
  • neighborhood preserving dictionary
  • pairwise distance
  • temporal adjacent bag of words (TA-BoW)

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