| Summary: | 碩士 === 國立交通大學 === 資訊科學系所 === 93 === Infrared imagery offers a promising alternative to visible light imagery in various applications owing to its capability of sensing object heat emissions in the distance. It is thus particularly suitable for security surveillances in the dark and for temperature inspections. In this thesis, we first investigate the characteristics of infrared imaging. Then, for visual surveillance applications, we develop region growing-based methods to segment human bodies in real-time. Different from popular background subtraction techniques for separating foreground objects, the proposed methods are based on temperature distributions to grow target regions and have no need to maintain a background model of the view field. Besides, head positions can thereafter be allocated using the segmented shape information. Experimental results show our methods can segment human shapes and allocate their heads correctly in most cases and achieve the real-time performance.
|
|---|
