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26 July 2018 Crowd counting system by facial recognition using Histogram of Oriented Gradients, Completed Local Binary Pattern, Gray-Level Co-Occurrence Matrix and Unmanned Aerial Vehicle
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Proceedings Volume 10828, Third International Workshop on Pattern Recognition; 108280Y (2018) https://doi.org/10.1117/12.2502020
Event: Third International Workshop on Pattern Recognition, 2018, Jinan, China
Abstract
A counting system is a device used for identifying the number of people present in a crowd. It has a wide variety of uses from fields of statistics, business and social sciences. This study introduces a method of a facial recognition counting system through the use of an unmanned aerial vehicle to capture aerial images of the crowd and the use of MATLAB to process those images to count the number of people present in the crowd. The algorithms used in this paper are Histogram of Oriented Gradients (HOG) and Completed Local Binary Pattern (CLBP) for low density and Gray Level Co-Occurrence Matrix (GLCM) for high density. From the data gathered, the program can classify an object as a head if it can see all of the human facial features like e.g. eyes, nose, mouth, etc. Thus, to obtain the best results in counting people in a crowd using this method, the user must take pictures at an angle and height where the features of the face can be seen, in our case, at 15 degrees and 3.2 meters respectively. But, if applied in an actual field, many people will be facing different directions and some faces will be blocked by other people.
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Jessie R. Balbin, Ramon G. Garcia, Kaira Emi D. Fernandez, Nicolo Paolo G. Golosinda, Karyl Denise G. Magpayo, and Robee Jasper B. Velasco "Crowd counting system by facial recognition using Histogram of Oriented Gradients, Completed Local Binary Pattern, Gray-Level Co-Occurrence Matrix and Unmanned Aerial Vehicle", Proc. SPIE 10828, Third International Workshop on Pattern Recognition, 108280Y (26 July 2018); https://doi.org/10.1117/12.2502020
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