Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/154
Title: Human action recognition with bag of visual words using different machine learning methods and hyperparameter optimization
Authors: Aslan, Muhammet Fatih
Durdu, Akif
Sabancı, Kadir
Keywords: Human Activity Recognition
Image Processing
Speeded Up Robust Features
Bag Of Visual Words
Machine Learning
K-Nearest Neighbors
Decision Tree
Support Vector Machine
Naive Bayes
Hyperparameter Optimization
Recognizing Human Actions
Robust Approach
Context
System
Image
Issue Date: 2020
Publisher: SPRINGER LONDON LTD
Abstract: Human activity recognition (HAR) has quite a wide range of applications. Due to its widespread use, new studies have been developed to improve the HAR performance. In this study, HAR is carried out using the commonly preferred KTH and Weizmann dataset, as well as a dataset which we created. Speeded up robust features (SURF) are used to extract features from these datasets. These features are reinforced with bag of visual words (BoVW). Different from the studies in the literature that use similar methods, SURF descriptors are extracted from binary images as well as grayscale images. Moreover, four different machine learning (ML) methods such as k-nearest neighbors, decision tree, support vector machine and naive Bayes are used for classification of BoVW features. Hyperparameter optimization is used to set the hyperparameters of these ML methods. As a result, ML methods are compared with each other through a comparison with the activity recognition performances of binary and grayscale image features. The results show that if the contrast of the environment decreases when a human enters the frame, the SURF of the binary image are more effective than the SURF of the gray image for HAR.
URI: https://doi.org/10.1007/s00521-019-04365-9
https://hdl.handle.net/20.500.13091/154
ISSN: 0941-0643
1433-3058
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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