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Erschienen in:
Practical Matters in Computer Vision Kapitel lesen Erstes Kapitel lesen

2015 | OriginalPaper | Buchkapitel

2. Human Action Recognition: Contour-Based and Silhouette-Based Approaches

verfasst von : Salim Al-Ali, Mariofanna Milanova, Hussain Al-Rizzo, Victoria Lynn Fox

Erschienen in: Computer Vision in Control Systems-2

Verlag: Springer International Publishing

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Abstract

Human action recognition in videos is a desired field in computer vision applications since it can be applied in human computer interaction, surveillance monitors, robot vision, etc. Two approaches of features are investigated in this chapter. First approach is a contour-based type. Four features are investigated in this approach such as Cartesian Coordinate Features (CCF), Fourier Descriptors Features (FDF), Centroid-Distance Features (CDF), and Chord-Length Features (CLF). The second approach is a silhouette-based type. Three features are investigated in this approach such as Histogram of Oriented Gradients (HOG), Histogram of Oriented Optical Flow (HOOF), and Structural Similarity Index Measure (SSIM) features. All these features are simple to compute, efficient to classify, and fast to calculate. Therefore, these features demonstrate a promising field for human action recognition. Moreover, the classification is achieved using two classifiers: K-Nearest-Neighbor (KNN) and Support Vector Machine (SVM). The experimental results demonstrated that these features have a promising potential and useful for the human action recognition in videos.

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Vorheriges Kapitel Practical Matters in Computer Vision
Nächstes Kapitel The Application of Machine Learning Techniques to Real Time Audience Analysis System
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Metadaten
Titel
Human Action Recognition: Contour-Based and Silhouette-Based Approaches
verfasst von
Salim Al-Ali
Mariofanna Milanova
Hussain Al-Rizzo
Victoria Lynn Fox
Copyright-Jahr
2015
Buch
Computer Vision in Control Systems-2

Print ISBN: 978-3-319-11429-3

Electronic ISBN: 978-3-319-11430-9

Copyright-Jahr: 2015

DOI
https://doi.org/10.1007/978-3-319-11430-9_2