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Deep Convolutional Neural Network based Person Detection and People Counting System |
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PP: 21-25 |
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doi:10.18576/aeta/110114
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Author(s) |
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Maksat Kanatov,
Lyazzat Atymtayeva,
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Abstract |
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| Nowadays, computer vision is an actively developing and one of the most important part of Artificial Intelligence. There
are a lot of works in this area. Computer Vision has a wide range of uses. For example, in medicine it can be used for diagnosing a
Magnetic Resonance Imaging or X-ray image, in security systems - for detecting intruders, for driverless cars or robotics to navigate in
space, etc. However, often image recognition works together with object detection. Usually required object for recognition takes only
the small part of original image whereas the rest part of the image does not carry useful information for recognizing. By this reason
to optimize computation time, we need to find this object, before recognizing. There are various methods and technologies for object
detection in the image. This work demonstrates one of the actual method in computer vision which named Deep Convolutional Neural
Networks and shows the advantages of this method in person detection and people counting.
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