AbstractsComputer Science

Various kinds of algorithms have been developed for object tracking, which can be divided into two categories, probabilistic and non-probabilistic, respectively. In either case, existing algorithms sometimes need to be improved to meet the challenges of a particular application, such as tracking abrupt motions of the target, changing lighting conditions of the environments, existing objects with similar appearance in the background, and etc. A good algorithm has to be robust for a particular application usually resulting in a trade-off between robustness and efficiency. In our research topic, we have developed a system to efficiently track the motion of the tip of the index finger, for the purpose of replacing the mouse and pad of a computer for HCI. We call this setup Finger Mouse implementation. The fingertip is marked by red using an electrical tape, and the background is the surface of the desk where the computer lays. We have developed a modified priori motion model for the particle filtering algorithm based on the analysis of natural motion of human fingertip movement. Our high-order autoregressive model combined with temporal velocity performs more accurately and efficiently for fingertip tracking, compared with the existing methods. The results of this research will be very useful. In addition to providing an alternative to healthy individuals, it is particularly suitable for disabled people who cannot mechanically move the mouse but use fingertip to express his/her intention of moving the cursor.