Segmentation of model-free objects carried by human hand: Intended for human-robot interaction applications

Most of robot applications which require interaction with human intend to hand over different objects between the both parties. In general, most of previous systems have supposed that the transfer task will be exclusively performed by human. However, how the task will be performed if the human is blind, elderly, disabled or concentrating on something else? In this case the transfer task should be exclusively controlled by robot, where the human could be considered as the weakest part. This paper will present vision algorithms which help the robot to recognize and to segment any object which is carried by the human hand in order to hand it over from the human hand even if the human is disabled, blind etc. The proposed vision algorithms are able to detect and to segment the carried objects with no idea about the model of the object in a very short cycle time, even if they are textureless, if the objects have the same color as the human skin and if the light conditions are changed strongly. The proposed algorithms are supported by successful results on different kinds of object.