We predicted human emotion using a Genetic Algorithm (GA) based lip feature extractor from facial images to classify
all seven universal emotions of fear, happiness, dislike, surprise, anger, sadness and neutrality. First, we isolated the
mouth from the input images using special methods, such as Region of Interest (ROI) acquisition, grayscaling, histogram
equalization, filtering, and edge detection. Next, the GA determined the optimal or near optimal ellipse parameters that
circumvent and separate the mouth into upper and lower lips. The two ellipses then went through fitness calculation and
were followed by training using a database of Japanese women's faces expressing all seven emotions. Finally, our
proposed algorithm was tested using a published database consisting of emotions from several persons. The final results
were then presented in confusion matrices. Our results showed an accuracy that varies from 20% to 60% for each of the
seven emotions. The errors were mainly due to inaccuracies in the classification, and also due to the different
expressions in the given emotion database. Detailed analysis of these errors pointed to the limitation of detecting
emotion based on the lip features alone. Similar work  has been done in the literature for emotion detection in only
one person, we have successfully extended our GA based solution to include several subjects.
We address spatial ontologies for the areas of operations of tactical behaviors carried out by unmanned ground vehicles
(UGVs). An ontology is a conceptualization of a domain and provides a common vocabulary for automated applications
in the domain of interest. Ontological concepts are typically qualitative yet are rigorously defined. An ontology should
provide abstract concepts that allow meaningful generalizations. The work reported here is the first known attempt to
apply spatial ontologies to tactical behaviors. Some research on spatial ontologies is based on point set topology,
although many find points to be unnatural primitives. Alternatives include relations defined in terms of the primitive
binary relation "connected_to" on regions; the "part_of" relation is also important. This paper includes a focused survey
driven by examples in which we evaluate the strengths and weaknesses of the different approaches for the domain in
question. We also develop new concepts and techniques especially applicable to representing and reasoning about areas
of operation in which UGVs perform missions.
This paper examines the applicability of genetic algorithms in the complete design of fuzzy logic controllers. While GA has been used before in the development of rule sets or high performance membership functions, the interdependence between these two components dictates that they should be designed together simultaneously. GA is fully capable of creating complete fuzzy controllers given the equations of motion of the system, eliminating the need for human input in the design loop. We show the application of this new method to the development of a cart controller.