Object recognition based on shape and function
Akihiro Eguchi · Journal of the Arkansas Academy of Science · 2013
This thesis explores a new approach to computational object recognition by borrowing an idea from child language acquisition studies in developmental psychology. Whereas previous image recognition research used shape to recognize and label a target object, the model proposed in this thesis also uses the function of the object resulting in a more accurate recognition. This thesis makes use of new gaming technology, Microsoft’s Kinect, in implementing the proposed new object recognition model. A demonstration of the model developed in this project properly infers different names for similarly shaped objects and the same name for differently shaped objects.