A modified EM algorithm for hand gesture segmentation in RGB-D data
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
This paper proposes a novel method with a modified Expectation-Maximisation (EM) Algorithm to segment hand gestures in the RGB-D data captured by Kinect. With the depth map and RGB image aligned by the genetic algorithm to estimate the key points from both depth and RGB images, a novel approach is proposed to refine the edge of the tracked hand gesture, which is used to segment the RGB image of the hand gestures, by applying a modified EM algorithm based on Bayesian networks. The experimental results demonstrated the modified EM algorithm effectively adjusts the RGB edges of the segmented hand gestures. The proposed methods have potential to improve the performance of hand gesture recognition in Human-Computer Interaction (HCI).
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) |
| Publisher | IEEE |
| Pages | 1736-1742 |
| ISBN (Electronic) | 978-1-4799-2072-3 |
| DOIs | |
| Publication status | Published - 8 Sep 2014 |
| Event | 2014 IEEE International Conference on Fuzzy Systems - Beijing, China Duration: 6 Jul 2014 → 11 Jul 2014 |
Publication series
| Name | |
|---|---|
| ISSN (Print) | 1098-7584 |
Conference
| Conference | 2014 IEEE International Conference on Fuzzy Systems |
|---|---|
| Abbreviated title | FUZZ-IEEE 2014 |
| Country | China |
| City | Beijing |
| Period | 6/07/14 → 11/07/14 |
Documents
- A Modified EM Algorithm for Hand Gesture Segmentation in
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Accepted author manuscript (Post-print), 2.91 MB, PDF document
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