Hand-Object Sense

Abstract

Hand-held objects play an important role in human-human and human-machine interaction. It can be used as a reference for understanding user intentions or user requirements. In this technical demonstration, we introduce an object recognition system called Hand-Object Sense that can automatically recognize the object held by user. This system first detects and segments the hand-held object by exploiting skeleton information combined with depth information. Second, in the object recognition stage, this system exploits features computed in different ways and fuses them to improve the recognition accuracy. Our system can recognize objects in real-time and have a good tolerance to angle and scale transformation. Furthermore, it has a good generalization capability for unknown objects.