Recognition of basic hand gestures on a horizontal surface using a single camera

dc.contributor.authorSarybay O.
dc.date.accessioned2024-12-19T12:14:03Z
dc.date.available2024-12-19T12:14:03Z
dc.date.issued2022
dc.description.abstractThe horizontal hand gesture recognition is an innovative, cheaper way for human-computer interaction. Currently, most researchers work with sensors, devices for hand gesture recognition, which require more resources. Instead, the presented horizontal method for hand gesture signal recognition by frames. A key element of this work is the research of a recognition algorithm using only a single camera. In the presented framework, the hand detection works as a converting BGR image to RGB before processing. Then, the palm and fingers are segmented so as to detect and recognize the fingers. There are handedness and hand landmarks on the image as a result of a hand detection. Each point of the landmark has coordination x, y, z values. There is a comparison algorithm of points to recognize hand gestures by fingers. The model has been implemented by getting landmark values on a data set of hand images, which are collected from video frames. In the presented framework, the hand detection works with computer vision (CV) algorithms, in general MediaPipe as a converting blue, green, red (BGR) image to red, green, blue (RGB) before processing. There are handedness and hand landmarks on the image as a result of a hand detection. Each point of the landmark has coordination x, y, z values. The performance of the method highly depends on the result of hand detection on the horizontal surface and collected dataset.
dc.identifier.urihttps://repository.sdu.edu.kz/handle/123456789/1593
dc.language.isoen
dc.subjecthuman-computer interaction, hand gesture, signal recognition by frames, algorithm, camera, dataset
dc.titleRecognition of basic hand gestures on a horizontal surface using a single camera
dc.typeOther

Files

Original bundle
Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
Orazaiym Sarybay.pdf
Size:
7.81 MB
Format:
Adobe Portable Document Format
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
12.6 KB
Format:
Item-specific license agreed to upon submission
Description:

Collections