Fingertips detection for human interaction system

Fingertips of human hand play an important role in hand-based interaction with computers. Identification of fingertips' positions in hand images is vital for developing a human computer interaction system. This paper proposes a novel method for detecting fingertips of a hand image analyzing the concept of the geometrical structural information of fingers. The research is divided into three parts: First, hand image is segmented for detecting hand, Second, invariant features (curvature zero-crossing points) are extracted from the boundary of the hand, Third, fingertips are detected. Experimental results show that the proposed approach is promising.

Detection of fingertips based on the combination of color information and circle detection

Fingertips of human hand play an important role in hand-based interaction with computers. Therefore, identification of fingertips' positions on hand image is vital for developing a human computer interaction system. All most all of the research works for fingertips detection, initially isolate hand image from the background image. Most of these techniques develop color based segmentation methods because human skin color possess an exceptional characterises that can be used to isolate hand from the rest of the image quite easily. Sometimes color image segmentation becomes difficult due to illumination and background variations. To make it simple and reliable, this paper proposes a robust method for detecting fingertips of a hand image based on the combination of color segmentation and circle detection. Due to the characteristics of circularity of fingertips regions of hand boundary, any existing circle detection algorithms can be applied to detect circles at fingertips region. It is difficult to detect fingertips solely based on the circle detection method. For this reason, initially the proposed method detects all the circular regions on the image applying Circle Hough Transformation (CHT) then the fingertips are selected based on the color characteristics of the fingertips regions. Experimental results show that the proposed approach is promising.

A multi-point haptic platform for grasping and manipulating virtual objects

This work presents a multi-point haptic platform that employs two Phantom Omni haptic devices. A gripper attachment connects to both devices and enables multi-point haptic grasping in virtual environments. In contrast to more complex approaches, this setup benefits from low-cost, reliability, and ease of programming while being capable of independently rendering forces to each of the user’s fingertips. The ability to grasp with multiple points potentially lends itself to applications such as virtual training, telesurgery and telemanipulation.