Abstract
This paper presents a vision based pose estimation system using knowledge based approach for human-robot symbiosis. The system is based on visual information of the face by connected component analysis of the skin color segmentation of images in HSV color model and is commenced with the face recognition and pose classification scheme using subspace PCA based pattern-matching strategies. With the knowledge of the known user's profile, face poses are then classified by multilayer perceptron. Based on the frame-based knowledge representation approach, face poses are being interpreted using the Software Platform for Agent and Knowledge (SPAK) management. On face pose recognition, robot is then instructed to perform some specific tasks by issuing pose commands. Experimental results demonstrate that the subspace method is better than that of the standard PCA method for face pose classification. The system has been demonstrated with the implementation of the algorithm to interact with an entertainment robot named, AIBO for human-robot symbiotic relationship.
Highlights
The meaning of the word ‘symbiosis’ as defined in the American heritage dictionary is “A close prolonged association among two or more different organisms of different species that may but does not necessarily benefit each member” (The American Heritage Dictionary, 2006)
Most of the researchers attack this kind of problem with face localization and feature selection with frontal view faces and without facial expression and normal lighting conditions the variation between the images of the same face is too large due to facial expression, hair style, pose variation, lighting conditions, make-up, etc
The algorithm is capable of detecting the faces in the images with different backgrounds and lighting conditions
Summary
The meaning of the word ‘symbiosis’ as defined in the American heritage dictionary is “A close prolonged association among two or more different organisms of different species that may but does not necessarily benefit each member” (The American Heritage Dictionary, 2006). This paper proposes a facial pose recognition based human–robot nonverbal interaction system to communicate with robots more likely to human. All of the above papers did not consider knowledge-based approach to interpret facial pose for person- specific human-robot interaction. This paper explores a face pose estimation system for person-specific human-robot interaction (HRI) through a knowledge-based approach. After applying the skin color segmentation process, binary image is obtained from which largest connected component is being analyzed for face detection. Since the skin-colors are clustered in color space and differ from person to person and of different races, the threshold value is determined from the hue histogram of the respective image In this experiment, the hue components have been chosen as: 0o < h face < 40o for the segmentation of skin-like regions. The face poses are recognized according to the matching results of the images at particular frame
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