Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
A Performance Evaluation of Local Descriptors
IEEE Transactions on Pattern Analysis and Machine Intelligence
Contour detection based on nonclassical receptive field inhibition
IEEE Transactions on Image Processing
Recognition of household objects by service robots through interactive and autonomous methods
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
| Hi-index | 0.00 |
Service robots need object recognition strategy that can work on various objects and backgrounds. Since no single method can work well in various situations, we need to combine several methods so that the robots can use an appropriate one automatically. In this paper we propose a scheme to classify situations depending on the characteristics of object of interest, background and user demand. We classify the situations into three categories and employ different techniques for each one. We use SIFT and biologically motivated object recognition techniques developed by Serre et al. for two categories. These two methods do not work well on the remaining category of situations. We propose a contour based technique for this remaining category. Through our experiments, we show that the contour based method performs better than the previously mentioned two methods for this category of situations.