Human activity recognition based on morphological dilation followed by watershed transformation method

Muhammad Hameed Siddiqi, Muhammad Fahim, Sungyoung Lee, Young Koo Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

Efficiency and accuracy are the most important terms for human activity recognition. Most of the existing works have the problem of speed. This paper proposed an efficient algorithm to recognize the activities of the human. There are three stages of this paper, segmentation, feature extraction and recognition. In this paper our contribution is in segmentation stage (based on morphological dilation) and in feature extraction stage (using watershed transformation). The proposed algorithm has been tested on six different types of activities (containing 420 frames). The recognition performance of our method has been compared with the existing method using Principle Component Analysis (PCA) to derive activity features. The results of our proposed method are comparable with the existing work. But in-term of efficiency, our algorithm was much faster than the existing work. The average accuracy and efficiency of the proposed algorithm for recognition was 80.83 % and 302.2 ms respectively.

Original languageEnglish
Title of host publicationICEIE 2010 - 2010 International Conference on Electronics and Information Engineering, Proceedings
PagesV2433-V2437
DOIs
Publication statusPublished - 2010
Externally publishedYes
Event2010 International Conference on Electronics and Information Engineering, ICEIE 2010 - Kyoto, Japan
Duration: 01 Aug 201003 Aug 2010

Publication series

NameICEIE 2010 - 2010 International Conference on Electronics and Information Engineering, Proceedings
Volume2

Conference

Conference2010 International Conference on Electronics and Information Engineering, ICEIE 2010
Country/TerritoryJapan
CityKyoto
Period01/08/201003/08/2010

Bibliographical note

Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.

Keywords

  • Component
  • Computer vision
  • Human activity recognition
  • Image segmentation
  • Morphological dilation
  • Watershedding

ASJC Scopus subject areas

  • Information Systems
  • Electrical and Electronic Engineering

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