Table of Contents
Fetching ...

UbiTouch: Towards a Universal Touch Interface

Dev Shah

TL;DR

This work targets ubiquitous computing by enabling touch interactions on arbitrary surfaces using a single thermal camera. The core approach, UbiTouch, combines a two-pass ROI-driven touch-detection pipeline with lightweight, vision-based processing to differentiate hover from touch, support multi-finger inputs, and reconstruct trajectories, while also addressing jitter through sensor fusion. Key contributions include a practical thermal-imaging–based framework that minimizes computational load and hardware requirements, enabling scalable interaction in diverse environments, with promising preliminary accuracy. The work lays groundwork for on-device, surface-agnostic touch sensing and points to future enhancements via RGB cues, improved hand detection, and large-scale testing to bolster robustness and applicability in real-world settings.

Abstract

Touch is one of the most intuitive ways for humans to interact with the world, and as we advance toward a ubiquitous computing environment where technology seamlessly integrates into daily life, natural interaction methods are essential. This paper introduces UbiTouch, a system leveraging thermal imaging to detect touch interactions on arbitrary surfaces. By employing a single thermal camera, UbiTouch differentiates between hovering and touch, detects multi-finger input, and completes trajectory tracking. Our approach emphasizes the use of lightweight, low-computation algorithms that maintain robust detection accuracy through innovative vision-based processing. UbiTouch aims to enable scalable, sustainable, and adaptable interaction systems for diverse applications, particularly with regards to on-human sensing.

UbiTouch: Towards a Universal Touch Interface

TL;DR

This work targets ubiquitous computing by enabling touch interactions on arbitrary surfaces using a single thermal camera. The core approach, UbiTouch, combines a two-pass ROI-driven touch-detection pipeline with lightweight, vision-based processing to differentiate hover from touch, support multi-finger inputs, and reconstruct trajectories, while also addressing jitter through sensor fusion. Key contributions include a practical thermal-imaging–based framework that minimizes computational load and hardware requirements, enabling scalable interaction in diverse environments, with promising preliminary accuracy. The work lays groundwork for on-device, surface-agnostic touch sensing and points to future enhancements via RGB cues, improved hand detection, and large-scale testing to bolster robustness and applicability in real-world settings.

Abstract

Touch is one of the most intuitive ways for humans to interact with the world, and as we advance toward a ubiquitous computing environment where technology seamlessly integrates into daily life, natural interaction methods are essential. This paper introduces UbiTouch, a system leveraging thermal imaging to detect touch interactions on arbitrary surfaces. By employing a single thermal camera, UbiTouch differentiates between hovering and touch, detects multi-finger input, and completes trajectory tracking. Our approach emphasizes the use of lightweight, low-computation algorithms that maintain robust detection accuracy through innovative vision-based processing. UbiTouch aims to enable scalable, sustainable, and adaptable interaction systems for diverse applications, particularly with regards to on-human sensing.

Paper Structure

This paper contains 9 sections, 5 figures, 1 algorithm.

Figures (5)

  • Figure 1: UbiTouch in action (image captured of a specific frame from a video). (Left) The raw thermal camera output streamed from a FLIR One Camera, showing the temperature difference between a wall and the human hand. (Right) Post processed binary image extracted along with successful detection of a touch (green box) along with fingertips (green dots).
  • Figure 2: Theory of operation for touch detection.
  • Figure 3: Fingertip and hand detection. (Left) The raw thermal camera output. (Middle left) Post processed binary image. (Middle right) Thermal image with the hand contour (green) and fingertips (blue) marked. (Right) ROIs along with histogram of fingertips marked.
  • Figure 4: Side-by-side figures showing both methods of touch detection.
  • Figure :