Human detection in indoor environment is essential for Robots working together with humans in
collaborative manufacturing environment. Similarly, Human detection is essential for service
robots providing service with household chores or helping elderly population with different daily
activities.
Human detection can be achieved by Human Head detection, as head is the most discriminative
part of human. Head detection method can be divided into three types: i) Method based on color
mode; ii) Method based on template matching; and iii) Method based on contour detection.
Method based on color mode is simple but is error prone. Method based on head template detects
head in the image by searching for a template which is similar to head template. On the other
hand, Method based on contour detection uses some information to describe head or head and
shoulder information. The use of only one criteria may not be sufficient and accuracy of human
head detection can be increased by combining the shape and color information. In this thesis, a
method of human detection is proposed by combining the head shape and skin color (i.e.,
Combination of method based on Color mode and method based on Contour detection). Mainly,
curvature criteria is used to segment out curves having similar curvature to find human head.
Further, skin color is detected to localize face in image plane. A curve represents human head
curve if only it has sufficient skin colored pixel in its closed proximity. Thus, by using color and
human head curvature it was found that promising results could be obtained in human detection
in indoor environment.
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After detecting humans in the surrounding, the next step for the robot could be to identify and
recognize them. In this thesis, the use of Gabor filter response on nine points was investigated to
identify eight different individuals. This suggests that the Gabor filter on nine points could be
applied to identify people in small areas, for example home or small office with less individuals.Masters of Applied Science (M.A.Sc.) in Natural Resource Engineerin
