Live Demonstration: Real-Time Multi-Hand Segmentation on Exhibition

• Published in: 2021 IEEE International Symposium on Circuits and Systems (ISCAS) p. 1
• Main Authors: Tsai, Tsung-Han, Huang, Shih-An
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-05-2021
• Subjects: Circuits and systems; hand segmentation; Image color analysis; Image segmentation; Neural networks; Real-time systems; Robustness; Skin; skin color; TX2
• ISBN: 9781728192017; 1728192013
• ISSN: 2158-1525; 2158-1525
• DOI: 10.1109/ISCAS51556.2021.9401231

In this paper, we proposed a multi-hand segmentation on exhibition. In exhibition there are many objects with similar color such as skin clothes and the decoration close to skin color. First we made a lot of virtual image to make the datasets closed to the exhibition, and combined the palm and back of hand into same picture. Secondly we proposed a robustness neural network call "Unet- Encoder Network (Unet-EN)" to train this datasets. We use pruning method to reduce the parameter and increase the speed. We implemented on NVIDIA¯ Jetson™ TX2. As a result, it can be implemented on some skin color space and supported multi-hand segmentation.