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A novel framework of continuous human-activity recognition using Kinect

  • Published:2018-10 Issue: Volume:311 Page:99-111
  • ISSN:0925-2312
  • Container-title:Neurocomputing
  • language:en
  • Short-container-title:Neurocomputing

Author:

Saini RajkumarORCID,Kumar PradeepORCID,Roy Partha Pratim,Dogra Debi ProsadORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Cognitive Neuroscience,Computer Science Applications

Reference45 articles.

1. Human action recognition in videos using kinematic features and multiple instance learning;Ali;IEEE Trans. Pattern Anal. Mach. Intell.,2010

2. Object trajectory-based activity classification and recognition using hidden Markov models;Bashir;IEEE Trans. Image Process.,2007

3. G3d: a gaming action dataset and real time action recognition evaluation framework;Bloom,2012

4. Action recognition from depth sequences using depth motion maps-based local binary patterns;Chen,2015

5. Improving human action recognition using fusion of depth camera and inertial sensors;Chen;IEEE Trans. Hum. Mach. Syst.,2015

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3. Clustering-based multi-featured self-supervised learning for human activities and video retrieval;Applied Intelligence;2024-04

4. Human Action Recognition Systems: A Review of the Trends and State-of-the-Art;IEEE Access;2024

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