A Real-time Eyesight Awareness Chip for Home Appliance Control

• Main Authors: Po-Han Song, 宋柏翰
• Other Authors: Chao-Lieh Chen
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/ag884n

碩士 === 崑山科技大學 === 電子工程研究所 === 97 === This paper proposes a low-cost real-time eyesight recognition algorithm for single user and its Silicon Intellectual Property (SIP) prototype in FPGA for single-chip integration of multimodal man-machine interfaces. This system mainly uses human’s eyesight to switch among machines such as home appliances. The eyesight is defined as the ability to switch from seeing one target to another. The system recognizes change of line of sights and incooperate with controller to control the target appliance. Traditional face detection and recognition methods require complex algorithms to calculate facial features and then find the eyes. Therefore, it is not practical to implement these algorithms into hardware integrated circuits because they are time-consuming and requires too much chip area. We exploit the nature that human eye blinks when line of sight changes to simplify complexity of algorithms. For hardware realization, we propose a buffering technique which is synchronous to pixel input from CCD. Therefore, we avoid external memory to save circuit area and power consumptions caused by large amount of memory accesses. Regarding Cb-Y-Cr pixel input information from the CCD camera, we use Sobel operator to detect the edge of the input image, use filtered image differences to find the moving area of the image, and detect eyes blinks by calculating chrominance change to find the location of the eyes. In order to verify the system''s function and performance, we combine a gesture recognition system for home appliance control as an application example. Users need neither any remote control nor any wearable device. With single CCD camara, a user use the most nature blinks and hand movement to control the home appliances. We successfully implement the eyesight detection system into an SIP prototype with the Field Programmable Gate Array (FPGA). Gesture recognition can be integrated becoming a multimodal man-machine interface of a single-chip.