Fingertip detection approach on depth image sequences for interactive projection system

Abstract

This study presents a vision-based approach for fingertip tracking on multi-touch tabletop which combines infrared and depth image processing. This approach intends to tackle two main issues on tabletop interaction: improve the performance for real-time applications and increase fingertip detection accuracy. A prototype using this fingertip tracking method was implemented with a depth and infrared camera. This approach processes the user's arm, hands and fingertips images using depth-space constraints, as well as clustering. Fingertip positions are accurately corrected using additional infrared information. Quantitative results show high accuracy of fingertip detection, with lower error rates compared to previous studies. Also, increased capabilities for real-time multi-user interaction are further demonstrated through a set of response time tests.