Abstract
In this paper, our purpose is extending 2D multi-touch interaction to 3D space and presenting a universal multi-touch gestures for 3D space. We described a system that allows people to use their familiar multi-touch gestures in 3D space without touching surface. We called these midair gestures in 3D as 3D multi-touch-like gestures. There is no object or surface for user to touch in 3D space, so we use depth camera to detect fingers’ state and estimate whether finger in the “click down” or “click up”, which show user’s intention to interact with system. We use machine learning to recognize hand shapes. While we do not need to precessing the recognition all the time, we only recognize hand shape between “click down” or “click up”.
| Original language | English |
|---|---|
| Title of host publication | Human Interface and the Management of Information. Interaction, Visualization, and Analytics - 20th International Conference, HIMI 2018, Held as Part of HCI International 2018, Proceedings |
| Publisher | Springer-Verlag |
| Pages | 227-239 |
| Number of pages | 13 |
| ISBN (Print) | 9783319920429 |
| DOIs | |
| Publication status | Published - 2018 Jan 1 |
| Event | 20th International Conference on Human Interface and the Management of Information, HIMI 2018 Held as Part of HCI International 2018 - Las Vegas, United States Duration: 2018 Jul 15 → 2018 Jul 20 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10904 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 20th International Conference on Human Interface and the Management of Information, HIMI 2018 Held as Part of HCI International 2018 |
|---|---|
| Country | United States |
| City | Las Vegas |
| Period | 18/7/15 → 18/7/20 |
Fingerprint
Keywords
- Gesture
- Human-computer interaction
- Machine learning
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Realizing multi-touch-like gestures in 3D space. / Lu, Chunmeng; Zhou, Li; Tanaka, Jiro.
Human Interface and the Management of Information. Interaction, Visualization, and Analytics - 20th International Conference, HIMI 2018, Held as Part of HCI International 2018, Proceedings. Springer-Verlag, 2018. p. 227-239 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10904 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Realizing multi-touch-like gestures in 3D space
AU - Lu, Chunmeng
AU - Zhou, Li
AU - Tanaka, Jiro
PY - 2018/1/1
Y1 - 2018/1/1
N2 - In this paper, our purpose is extending 2D multi-touch interaction to 3D space and presenting a universal multi-touch gestures for 3D space. We described a system that allows people to use their familiar multi-touch gestures in 3D space without touching surface. We called these midair gestures in 3D as 3D multi-touch-like gestures. There is no object or surface for user to touch in 3D space, so we use depth camera to detect fingers’ state and estimate whether finger in the “click down” or “click up”, which show user’s intention to interact with system. We use machine learning to recognize hand shapes. While we do not need to precessing the recognition all the time, we only recognize hand shape between “click down” or “click up”.
AB - In this paper, our purpose is extending 2D multi-touch interaction to 3D space and presenting a universal multi-touch gestures for 3D space. We described a system that allows people to use their familiar multi-touch gestures in 3D space without touching surface. We called these midair gestures in 3D as 3D multi-touch-like gestures. There is no object or surface for user to touch in 3D space, so we use depth camera to detect fingers’ state and estimate whether finger in the “click down” or “click up”, which show user’s intention to interact with system. We use machine learning to recognize hand shapes. While we do not need to precessing the recognition all the time, we only recognize hand shape between “click down” or “click up”.
KW - Gesture
KW - Human-computer interaction
KW - Machine learning
UR - http://www.scopus.com/inward/record.url?scp=85050393106&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85050393106&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-92043-6_20
DO - 10.1007/978-3-319-92043-6_20
M3 - Conference contribution
SN - 9783319920429
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 227
EP - 239
BT - Human Interface and the Management of Information. Interaction, Visualization, and Analytics - 20th International Conference, HIMI 2018, Held as Part of HCI International 2018, Proceedings
PB - Springer-Verlag
ER -