Parallel distributed processing: explorations in the microstructure of cognition, vol. 1: foundations
Neural Networks for Pattern Recognition
Neural Networks for Pattern Recognition
Handbook of Neural Computation
Handbook of Neural Computation
Model-Based Object Recognition - A Survey of Recent Research
Model-Based Object Recognition - A Survey of Recent Research
Eigenregions for Image Classification
IEEE Transactions on Pattern Analysis and Machine Intelligence
Identification of objects from image regions
ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
Combining neural networks and clustering techniques for object recognition in indoor video sequences
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
Object recognition and tracking in video sequences: a new integrated methodology
CIARP'06 Proceedings of the 11th Iberoamerican conference on Progress in Pattern Recognition, Image Analysis and Applications
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This paper presents the results obtained in a real experiment for object recognition in a sequence of images captured by a mobile robot in an indoor environment. The purpose is that the robot learns to identify and locate objects of interest in its environment from samples of different views of the objects taken from video sequences. In this work, objects are simply represented as an unstructured set of spots (image regions) for each frame, which are obtained from the result of an image segmentation algorithm applied on the whole sequence. Each spot is semi-automatically assigned to a class (one of the objects or the background) and different features (color, size and invariant moments) are computed for it. These labeled data are given to a feed-forward neural network which is trained to classify the spots. The results obtained with all the features, several feature subsets and a backward selection method show the feasibility of the approach and point to color as the fundamental feature for discriminative ability.