Name
Abstract | ||
|---|---|---|
In this paper, we introduce an electronic shift lever control system based on hand pose recognition technology to provide a convenient and simple interface to drivers. The hand pose recognition algorithm consists of three processes. The first is hand localization using a simple approach based on deep learning. The second step is the prediction of the 3D hand joint location, and the final step is hand pose recognition. During this process, we define six hand poses and extract feature vectors obtained using the 3D offset from the center of the hand location to the hand joint location. The hand pose is then recognized using a simple KNN classifier. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/ICCE.2019.8661992 | 2019 IEEE International Conference on Consumer Electronics (ICCE) |
Field | DocType | ISSN |
Computer vision,Feature vector,Computer science,Lever,Artificial intelligence,Control system,Deep learning,Recognition algorithm,Classifier (linguistics),Offset (computer science) | Conference | 2158-3994 |
ISBN | Citations | PageRank |
978-1-5386-7910-4 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hyunduk Kim | 1 | 49 | 10.91 |
| Sang-Heon Lee | 2 | 105 | 22.48 |
| Myoung-Kyu Sohn | 3 | 33 | 7.17 |
| Wonju Bae | 4 | 0 | 0.34 |