Human activities recognition using shape moments and histogram of normalized distances “HND”
Joint Authors
Abd al-Munim, Husam
Ali, Jamal
Samir, Hanan
Source
Journal of Al-Azhar University Engineering Sector
Issue
Vol. 13, Issue 46 (31 Jan. 2018), pp.112-121, 10 p.
Publisher
al-Azhar University Faculty of Engineering
Publication Date
2018-01-31
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Topics
Abstract EN
This paper presents an algorithm for human activities recognition in videos based on a combination of two different feature types the first feature type concerns the shape and is called the shape moments.
the second feature type concerns the contour boundary coordinates and the feature is called histogram of normalized distances from center of gravity of the object Shape “COG” and its contour points “HND”.
combining these features leads to the formation of a strong complementary feature vector that captures effective discriminate details of human action videos.
we use two classifiers; the first is multi-class support vector machine and the second is naïve bayes classifier.
the recognition rate by using multi-class SVM classifier is up to 95.6% but by using naive bayes classifier is 97.2%.
American Psychological Association (APA)
Samir, Hanan& Abd al-Munim, Husam& Ali, Jamal. 2018. Human activities recognition using shape moments and histogram of normalized distances “HND”. Journal of Al-Azhar University Engineering Sector،Vol. 13, no. 46, pp.112-121.
https://search.emarefa.net/detail/BIM-918368
Modern Language Association (MLA)
Abd al-Munim, Husam…[et al.]. Human activities recognition using shape moments and histogram of normalized distances “HND”. Journal of Al-Azhar University Engineering Sector Vol. 13, no. 46 (Jan. 2018), pp.112-121.
https://search.emarefa.net/detail/BIM-918368
American Medical Association (AMA)
Samir, Hanan& Abd al-Munim, Husam& Ali, Jamal. Human activities recognition using shape moments and histogram of normalized distances “HND”. Journal of Al-Azhar University Engineering Sector. 2018. Vol. 13, no. 46, pp.112-121.
https://search.emarefa.net/detail/BIM-918368
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references>
Record ID
BIM-918368