Universiti Teknologi Malaysia Institutional Repository

Crowd detection from aerial images

Md. Zaini, Siti Ernee (2015) Crowd detection from aerial images. Masters thesis, Universiti Teknologi Malaysia, Faculty of Electrical Engineering.


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The detection of crowd from surveillance imagery is important to monitor public places and to ensure public safety. Hence, this work proposes crowd detection from static image captured from Unmanned Aerial Vehicle. The proposed methodology consists of three steps: FAST feature extraction, Gray Level Co-Occurrence Matrix (GLCM) feature computation and the use of Support Vector Machine (SVM) for classification. The use of FAST corner detector is to obtain regions of interest where possible existence of crowd. The application of GLCM is to extract second order statistical texture features for texture analysis. The result of GLCM then, will be classified to crowd and non-crowd using SVM. For evaluation, ten different images were used taken in various crowd formation, event and location. The accuracy of the proposed method is obtained and the classification results are shown visually.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Kejuruteraan (Elektrik - Komputer dan Sistem Mikroelektronik)) - Universiti Teknologi Malaysia, 2015; Supervisor : Dr. Usman Ullah Sheikh
Uncontrolled Keywords:aerial images, GLCM, Support Vector Machine (SVM)
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7885-7895 Computer engineer. Computer hardware
Divisions:Electrical Engineering
ID Code:48892
Deposited On:23 Nov 2015 04:28
Last Modified:05 Jul 2020 06:48

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