Onboard Real-time Object Surface Recognition for a Small Indoor Mobile Platform Based on Surface Component Ratio Histogram

Since a RGB-D sensor provides rich information about the scene, various object recognition schemes and low-level image descriptors can be used to improve the SLAM performance. However, a cleaning robot, which is usually flat and thus the camera is close to the floor, usually only has a partial view of the objects in front of the camera; therefore, conventional object recognition schemes based on the complete view of objects are not suitable. To address this problem, we introduce a novel object surface recognition algorithm based on the proposed surface component ratio histogram (SCRH). SCRH is a surface descriptor which describes the geometrical shape of the partial view of the object. Without any pre-trained model of the objects, SCRH provides a way to deal with the unexpected objects which the robot encounters during the navigation. SCRH was evaluated using several objects lying on the floor of which the identities are not known in advance. The experimental results show that objects are successfully discriminated based on their surfaces and SCRH is robust for object surface recognition.