Pointing at planar surfaces such as TV and computer monitors or projection screens can be a useful mode of interaction between humans and machines. To a large extent what seems to hinder the use of vision in such practical applications is the difficulty of the computational task, which is typically defined as 3-D reconstruction from uncalibrated 2-D images of a non-static scene. We describe below two designs where, using one or two cameras, the target of pointing on a flat monitor or screen is identified without 3-D inference, using only image morphing and line intersection. This is accomplished by registering the images with the target plane. When used to identify a pointing target on a surface hidden from the camera (e.g., a computer monitor which supports the camera itself as in most PC configurations), we add aperture(s) coplanar with the target surface in front of the camera(s). We describe experimental results showing a fully automated procedure for pointing target detection with high accuracy. The simplicity of our method and its robustness, as well as the relative accuracy of our results, can make pointing a practical means of human-machine interaction.

This article describes a 30 frames/second VGA format image sensor made in a standard CMOS process with an embedded massively parallel processor. The processor is fully programmable and therefore the sensor IC itself is able to run a variety of algorithms with data and processing in close vicinity of the sensor. Because of the parallel architecture comprising processor array and parallel memory accesses, high computational performances of up to 5 GOPS at 16 MHz are achieved. This high performance allowed us to implement skin tone detection on the camera itself as part of a larger system for face recognition, releasing the host computer of cumbersome pixel processing tasks and minimizing the data transfer between camera and computer.