Abstract
In this paper, we propose a method for 3D hand pose recognition using two omnidirectional cameras that enables users to perform proximity gesture operations in the entire range in front of a display. In this method, we use a technique of FOV division, which transforms an input omnidirectional camera image into multiple perspective projection images with virtually rotating the camera, in order to avoid distortion in the peripheral area of a perspective projection image. We also introduce two-stage skeleton detection, which uses the results of whole-body skeleton detection for determining the range of hand skeleton detection to reduce false detections. We evaluated the detection rate with and without FOV division. The detection rate with FOV division is higher than that without FOV division, and complex poses can be detected. In addition, the effectiveness of the two-stage skeleton detection was confirmed by comparing the results with and without the two-stage detection.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Kumar, P., Verma, J., Prasad, S.: Hand data glove: a wearable real-time device for human-computer interaction. Int. J. Adv. Sci. Technol. 43, 15–26 (2012)
Pietroszek, K., Tahai, L., Wallace, J.R., Lank, E.: Watchcasting: freehand 3d interaction with off-the-shelf smartwatch. In: Proceedings of 2017 IEEE Symposium on 3D User Interfaces (3DUI), pp. 172–175 (2017)
Mäkelä, V., James, J., Keskinen, T., Hakulinen, J., Turunen, M.: “ It’s natural to grab and pull’’: retrieving content from large displays using mid-air gestures. IEEE Pervas. Comput. 16(3), 70–77 (2017)
Raj, M., Creem-Regehr, S.H., Rand, K.M., Stefanucci, J.K., Thompson, W.B.: Kinect based 3d object manipulation on a desktop display. In: Proceedings of the ACM Symposium on Applied Perception, pp. 99–102 (2012)
Bizzotto, N., Costanzo, A., Bizzotto, L., Regis, D., Sandri, A., Magnan, B.: Leap motion gesture control with Osirix in the operating room to control imaging: first experiences during live surgery. Surg. Innov. 21(6), 655–656 (2014)
Fanini, B.: A 3D interface to explore and manipulate multi-scale virtual scenes using the leap motion controller. In: Proceedings of ACHI 2014, the Seventh International Conference on Advances in Computer-Human Interactions, pp. 258–263 (2014)
Yam-Viramontes, B.A., Mercado-Ravell, D.: Implementation of a natural user interface to command a drone. In: Proceedings of 2020 International Conference on Unmanned Aircraft Systems (ICUAS), pp. 1139–1144 (2020)
Cao, Z., Hidalgo, G., Simon, T., Wei, S.E., Sheikh, Y.: Openpose: realtime multi-person 2d pose estimation using part affinity fields. IEEE Trans. Pattern Anal. Mach. Intell. 43(1), 172–186 (2019)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Abe, Y., Komuro, T. (2022). 3D Hand Pose Recognition Over a Wide Area Using Two Omnidirectional Cameras with Field-of-view Division. In: Kurosu, M., et al. HCI International 2022 - Late Breaking Papers. Multimodality in Advanced Interaction Environments. HCII 2022. Lecture Notes in Computer Science, vol 13519. Springer, Cham. https://doi.org/10.1007/978-3-031-17618-0_1
Download citation
DOI: https://doi.org/10.1007/978-3-031-17618-0_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-17617-3
Online ISBN: 978-3-031-17618-0
eBook Packages: Computer ScienceComputer Science (R0)