3 research outputs found
Human detection and face recognition in indoor environment to improve human-robot interaction in assistive and collaborative robots
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
Optical control of in-plane domain configuration and domain wall motion in ferroelectric and ferroelastic
The sensitivity of ferroelectric domain walls to external stimuli makes them
functional entities in nanoelectronic devices. Specifically, optically driven
domain reconfiguration with in-plane polarization is advantageous and thus
highly sought. Here, we show the existence of in-plane polarized sub-domains
imitating a single domain state and reversible optical control of its domain
wall movement in a single-crystal of ferroelectric BaTiO3. Similar optical
control in the domain configuration of non-polar ferroelastic material
indicates long-range ferroelectric polarization is not essential for the
optical control of domain wall movement. Instead, flexoelectricity is found to
be an essential ingredient for the optical control of the domain configuration
and hence, ferroelastic materials would be another possible candidate for
nanoelectronic device applications