Object recognition and activity learning using kinect

Object recognition based on shape and function

2011 -


This project 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.


The objective of this research is to combine the Kinect sensor with machine learning techniques to implement an object recognition model that uses both shape bias and function bias to learn the names of objects in a manner similar to how human children acquire names of objects.


How human learn name of objects

Simulation of biases (Grabner, Gall, & Gool, 2011)


Shape bias with Kinect

Function Bias with Kinect

Object recognition using both shape and function bias