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Reducing the Latency of Touch Tracking on Ad-hoc Surfaces

Published: 14 November 2022 Publication History

Abstract

Touch sensing on ad-hoc surfaces has the potential to transform everyday surfaces in the environment - desks, tables and walls - into tactile, touch-interactive surfaces, creating large, comfortable interactive spaces without the cost of large touch sensors. Depth sensors are a promising way to provide touch sensing on arbitrary surfaces, but past systems have suffered from high latency and poor touch detection accuracy. We apply a novel state machine-based approach to analyzing touch events, combined with a machine-learning approach to predictively classify touch events from depth data with lower latency and higher touch accuracy than previous approaches. Our system can reduce end-to-end touch latency to under 70ms, comparable to conventional capacitive touchscreens. Additionally, we open-source our dataset of over 30,000 touch events recorded in depth, infrared and RGB for the benefit of future researchers.

Supplementary Material

Teaser (iss22main-id4514-p-teaser.mp4)
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References

[1]
Arturo Cadena, Rubén Carvajal, Bruno Guamán, Roger Granda, Enrique Peláez, and Katherine Chiluiza. 2016. Fingertip detection approach on depth image sequences for interactive projection system. In 2016 IEEE Ecuador Technical Chapters Meeting (ETCM). 1–6. https://doi.org/10.1109/ETCM.2016.7750827
[2]
Elie Cattan, Amélie Rochet-Capellan, and François Bérard. 2015. A Predictive Approach for an End-to-End Touch-Latency Measurement. In Proceedings of the 2015 International Conference on Interactive Tabletops & Surfaces (ITS ’15). Association for Computing Machinery, New York, NY, USA. 215–218. isbn:978-1-4503-3899-8 https://doi.org/10.1145/2817721.2817747
[3]
Elie Cattan, Amélie Rochet-Capellan, Pascal Perrier, and François Bérard. 2015. Reducing Latency with a Continuous Prediction: Effects on Users’ Performance in Direct-Touch Target Acquisitions. In Proceedings of the 2015 International Conference on Interactive Tabletops & Surfaces (ITS ’15). Association for Computing Machinery, New York, NY, USA. 205–214. isbn:978-1-4503-3899-8 https://doi.org/10.1145/2817721.2817736
[4]
Zhi Chai and Roy Shilkrot. 2018. Enhanced Touchable Projector-depth System with Deep Hand Pose Estimation. arXiv:1812.11090 [cs], Dec., arxiv:1812.11090 arXiv: 1812.11090
[5]
Jonathan Deber, Bruno Araujo, Ricardo Jota, Clifton Forlines, Darren Leigh, Steven Sanders, and Daniel Wigdor. 2016. Hammer Time! A Low-Cost, High Precision, High Accuracy Tool to Measure the Latency of Touchscreen Devices. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI ’16). Association for Computing Machinery, New York, NY, USA. 2857–2868. isbn:978-1-4503-3362-7 https://doi.org/10.1145/2858036.2858394
[6]
Andreas Dippon and Gudrun Klinker. 2011. KinectTouch: accuracy test for a very low-cost 2.5D multitouch tracking system. In Proceedings of the ACM International Conference on Interactive Tabletops and Surfaces (ITS ’11). Association for Computing Machinery, New York, NY, USA. 49–52. isbn:978-1-4503-0871-7 https://doi.org/10.1145/2076354.2076363
[7]
Florian Echtler, Manuel Huber, and Gudrun Klinker. 2008. Shadow tracking on multi-touch tables. In Proceedings of the working conference on Advanced visual interfaces (AVI ’08). Association for Computing Machinery, New York, NY, USA. 388–391. isbn:978-1-60558-141-5 https://doi.org/10.1145/1385569.1385640
[8]
Thomas B. Fitzpatrick. 1988. The Validity and Practicality of Sun-Reactive Skin Types I Through VI. Archives of Dermatology, 124, 6 (1988), June, 869–871. issn:0003-987X https://doi.org/10.1001/archderm.1988.01670060015008
[9]
Yuxiang Gao and Chien-Ming Huang. 2019. PATI: a projection-based augmented table-top interface for robot programming. In Proceedings of the 24th International Conference on Intelligent User Interfaces (IUI ’19). Association for Computing Machinery, New York, NY, USA. 345–355. isbn:978-1-4503-6272-6 https://doi.org/10.1145/3301275.3302326
[10]
Jun Gong, Aakar Gupta, and Hrvoje Benko. 2020. Acustico: Surface Tap Detection and Localization using Wrist-based Acoustic TDOA Sensing. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, New York, NY, USA. 406–419. isbn:978-1-4503-7514-6 https://doi.org/10.1145/3379337.3415901
[11]
Dan Gregor, Ondrej Prucha, Jakub Rocek, and Josef Kortan. 2017. Digital playgroundz. In ACM SIGGRAPH 2017 VR Village (SIGGRAPH ’17). Association for Computing Machinery, New York, NY, USA. 1–2. isbn:978-1-4503-5013-6 https://doi.org/10.1145/3089269.3089288
[12]
Yizheng Gu, Chun Yu, Zhipeng Li, Weiqi Li, Shuchang Xu, Xiaoying Wei, and Yuanchun Shi. 2019. Accurate and Low-Latency Sensing of Touch Contact on Any Surface with Finger-Worn IMU Sensor. In Proceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (UIST ’19). Association for Computing Machinery, New York, NY, USA. 1059–1070. isbn:978-1-4503-6816-2 https://doi.org/10.1145/3332165.3347947
[13]
Taku Hachisu and Hiroyuki Kajimoto. 2013. HACHIStack: dual-layer photo touch sensing for haptic and auditory tapping interaction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI ’13). Association for Computing Machinery, New York, NY, USA. 1411–1420. isbn:978-1-4503-1899-0 https://doi.org/10.1145/2470654.2466187
[14]
Ken Hinckley, Seongkook Heo, Michel Pahud, Christian Holz, Hrvoje Benko, Abigail Sellen, Richard Banks, Kenton O’Hara, Gavin Smyth, and William Buxton. 2016. Pre-Touch Sensing for Mobile Interaction. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI ’16). Association for Computing Machinery, New York, NY, USA. 2869–2881. isbn:978-1-4503-3362-7 https://doi.org/10.1145/2858036.2858095
[15]
Daisuke Iwai and Kosuke Sato. 2005. Heat sensation in image creation with thermal vision. In Proceedings of the 2005 ACM SIGCHI International Conference on Advances in computer entertainment technology (ACE ’05). Association for Computing Machinery, New York, NY, USA. 213–216. isbn:978-1-59593-110-8 https://doi.org/10.1145/1178477.1178510
[16]
Daniel Kurz. 2014. Thermal touch: Thermography-enabled everywhere touch interfaces for mobile augmented reality applications. In 2014 IEEE International Symposium on Mixed and Augmented Reality (ISMAR). 9–16. https://doi.org/10.1109/ISMAR.2014.6948403
[17]
Gierad Laput and Chris Harrison. 2019. SurfaceSight: A New Spin on Touch, User, and Object Sensing for IoT Experiences. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI ’19). Association for Computing Machinery, New York, NY, USA. 1–12. isbn:978-1-4503-5970-2 https://doi.org/10.1145/3290605.3300559
[18]
Jiajun Lu, Hrvoje Benko, and Andrew D. Wilson. 2017. Hybrid HFR Depth: Fusing Commodity Depth and Color Cameras to Achieve High Frame Rate, Low Latency Depth Camera Interactions. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems (CHI ’17). Association for Computing Machinery, New York, NY, USA. 5966–5975. isbn:978-1-4503-4655-9 https://doi.org/10.1145/3025453.3025478
[19]
Joe Marshall, Tony Pridmore, Mike Pound, Steve Benford, and Boriana Koleva. 2008. Pressing the Flesh: Sensing Multiple Touch and Finger Pressure on Arbitrary Surfaces. In Pervasive Computing, Jadwiga Indulska, Donald J. Patterson, Tom Rodden, and Max Ott (Eds.). 5013, Springer Berlin Heidelberg, Berlin, Heidelberg. 38–55. isbn:978-3-540-79575-9 978-3-540-79576-6 https://doi.org/10.1007/978-3-540-79576-6_3 Series Title: Lecture Notes in Computer Science
[20]
Takashi Matsubara, Naoki Mori, Takehiro Niikura, and Shun’ichi Tano. 2017. Touch detection method for non-display surface using multiple shadows of finger. In 2017 IEEE 6th Global Conference on Consumer Electronics (GCCE). 1–5. https://doi.org/10.1109/GCCE.2017.8229364
[21]
Manuel Meier, Paul Streli, Andreas Fender, and Christian Holz. 2021. TapID: Rapid Touch Interaction in Virtual Reality using Wearable Sensing. In 2021 IEEE Virtual Reality and 3D User Interfaces (VR). 519–528. https://doi.org/10.1109/VR50410.2021.00076 ISSN: 2642-5254
[22]
Sundar Murugappan, Vinayak, Niklas Elmqvist, and Karthik Ramani. 2012. Extended multitouch: recovering touch posture and differentiating users using a depth camera. In Proceedings of the 25th annual ACM symposium on User interface software and technology. Association for Computing Machinery, New York, NY, USA. 487–496. isbn:978-1-4503-1580-7 https://doi.org/10.1145/2380116.2380177
[23]
Takehiro Niikura, Takashi Matsubara, and Naoki Mori. 2016. Touch Detection System for Various Surfaces Using Shadow of Finger. In Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces (ISS ’16). Association for Computing Machinery, New York, NY, USA. 337–342. isbn:978-1-4503-4248-3 https://doi.org/10.1145/2992154.2996777
[24]
Vivian Shen, James Spann, and Chris Harrison. 2021. FarOut Touch: Extending the Range of ad hoc Touch Sensing with Depth Cameras. In Symposium on Spatial User Interaction (SUI ’21). Association for Computing Machinery, New York, NY, USA. 1–12. isbn:978-1-4503-9091-0 https://doi.org/10.1145/3485279.3485281
[25]
Ziwei Song, Yuichiro Kinoshita, Kentaro Go, and Gangyong Jia. 2021. Touch Point Prediction for Interactive Public Displays Based on Camera Images. In 2021 International Conference on Cyberworlds (CW). 133–136. https://doi.org/10.1109/CW52790.2021.00029 ISSN: 2642-3596
[26]
Naoki Sugita, Daisuke Iwai, and Kosuke Sato. 2008. Touch sensing by image analysis of fingernail. In 2008 SICE Annual Conference. 1520–1525. https://doi.org/10.1109/SICE.2008.4654901
[27]
Ryo Takahashi, Masaaki Fukumoto, Changyo Han, Takuya Sasatani, Yoshiaki Narusue, and Yoshihiro Kawahara. 2020. TelemetRing: A Batteryless and Wireless Ring-shaped Keyboard using Passive Inductive Telemetry. In Proceedings of the 33rd Annual ACM Symposium on User Interface Software and Technology. Association for Computing Machinery, New York, NY, USA. 1161–1168. isbn:978-1-4503-7514-6 https://doi.org/10.1145/3379337.3415873
[28]
Mayuka Tsuji, Hiroyuki Kubo, Suren Jayasuriya, Takuya Funatomi, and Yasuhiro Mukaigawa. 2021. Touch Sensing for a Projected Screen Using Slope Disparity Gating. IEEE Access, 9 (2021), 106005–106013. issn:2169-3536 https://doi.org/10.1109/ACCESS.2021.3099901 Conference Name: IEEE Access
[29]
Andrew D. Wilson. 2010. Using a depth camera as a touch sensor. In ACM International Conference on Interactive Tabletops and Surfaces (ITS ’10). Association for Computing Machinery, New York, NY, USA. 69–72. isbn:978-1-4503-0399-6 https://doi.org/10.1145/1936652.1936665
[30]
Haijun Xia, Ricardo Jota, Benjamin McCanny, Zhe Yu, Clifton Forlines, Karan Singh, and Daniel Wigdor. 2014. Zero-latency tapping: using hover information to predict touch locations and eliminate touchdown latency. In Proceedings of the 27th annual ACM symposium on User interface software and technology (UIST ’14). Association for Computing Machinery, New York, NY, USA. 205–214. isbn:978-1-4503-3069-5 https://doi.org/10.1145/2642918.2647348
[31]
Robert Xiao, Scott Hudson, and Chris Harrison. 2016. DIRECT: Making Touch Tracking on Ordinary Surfaces Practical with Hybrid Depth-Infrared Sensing. In Proceedings of the 2016 ACM International Conference on Interactive Surfaces and Spaces (ISS ’16). Association for Computing Machinery, New York, NY, USA. 85–94. isbn:978-1-4503-4248-3 https://doi.org/10.1145/2992154.2992173
[32]
Robert Xiao, Julia Schwarz, Nick Throm, Andrew D. Wilson, and Hrvoje Benko. 2018. MRTouch: Adding Touch Input to Head-Mounted Mixed Reality. IEEE Transactions on Visualization and Computer Graphics, 24, 4 (2018), April, 1653–1660. issn:1077-2626 https://doi.org/10.1109/TVCG.2018.2794222
[33]
Lixing Zhang and Takafumi Matsumaru. 2016. Near-Field Touch Interface Using Time-of-Flight Camera. Journal of Robotics and Mechatronics, 28, 5 (2016), Oct., 759–775. https://doi.org/10.20965/jrm.2016.p0759 Publisher: Fuji Technology Press Ltd.
[34]
Yang Zhang, Gierad Laput, and Chris Harrison. 2017. Electrick: Low-Cost Touch Sensing Using Electric Field Tomography. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery, New York, NY, USA. 1–14. isbn:978-1-4503-4655-9 https://doi.org/10.1145/3025453.3025842

Cited By

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  • (2024)TouchInsight: Uncertainty-aware Rapid Touch and Text Input for Mixed Reality from Egocentric VisionProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676330(1-16)Online publication date: 13-Oct-2024
  • (2024)TriPad: Touch Input in AR on Ordinary Surfaces with Hand Tracking OnlyProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642323(1-18)Online publication date: 11-May-2024
  • (2023)Structured Light Speckle: Joint Ego-Centric Depth Estimation and Low-Latency Contact Detection via Remote VibrometryProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606749(1-12)Online publication date: 29-Oct-2023

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    cover image Proceedings of the ACM on Human-Computer Interaction
    Proceedings of the ACM on Human-Computer Interaction  Volume 6, Issue ISS
    December 2022
    746 pages
    EISSN:2573-0142
    DOI:10.1145/3554337
    Issue’s Table of Contents
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    Publication History

    Published: 14 November 2022
    Published in PACMHCI Volume 6, Issue ISS

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    Author Tags

    1. ad-hoc surfaces
    2. latency reduction
    3. touch detection

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    View all
    • (2024)TouchInsight: Uncertainty-aware Rapid Touch and Text Input for Mixed Reality from Egocentric VisionProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676330(1-16)Online publication date: 13-Oct-2024
    • (2024)TriPad: Touch Input in AR on Ordinary Surfaces with Hand Tracking OnlyProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642323(1-18)Online publication date: 11-May-2024
    • (2023)Structured Light Speckle: Joint Ego-Centric Depth Estimation and Low-Latency Contact Detection via Remote VibrometryProceedings of the 36th Annual ACM Symposium on User Interface Software and Technology10.1145/3586183.3606749(1-12)Online publication date: 29-Oct-2023

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