Title :
Indoor object recognition through human interaction using wavelet features
Author :
Wang, QingHua ; Lopes, Luis Seabra
Author_Institution :
Instituto de Engenhria Electron. e Telematica de Aveiro, Portugal
Abstract :
In this paper a preliminary work towards grounded concept learning for a service robot through its vision and human interaction is presented. With a lifelong learning server (LLL), described in [L. S. Lopes and Q.H. Wang, 2002], the robot can incrementally learn to recognize instances of such concepts of indoor objects as "person ", "trash-can " and "triangle sign" using simple intra-band statistical features extracted from the Haar wavelet transform of its vision information under the instruction of a human teacher. Experimental results show that these simple wavelet-based features can efficiently describe the characteristics of different objects in an office-like environment. Comparison with some other feature extraction methods is also given.
Keywords :
Haar transforms; continuing professional development; feature extraction; human computer interaction; learning (artificial intelligence); object recognition; robot vision; wavelet transforms; Haar wavelet transform; feature extraction; human interaction; indoor object recognition; intraband statistical features; lifelong learning server; robot vision; wavelet features; Data mining; Discrete cosine transforms; Feature extraction; Human robot interaction; Intelligent robots; Object recognition; Service robots; Vehicle detection; Wavelet analysis; Wavelet transforms;
Conference_Titel :
Robotics, Intelligent Systems and Signal Processing, 2003. Proceedings. 2003 IEEE International Conference on
Print_ISBN :
0-7803-7925-X
DOI :
10.1109/RISSP.2003.1285568
