International Journal of Computer Vision
An active vision architecture based on iconic representations
Artificial Intelligence - Special volume on computer vision
Local Grayvalue Invariants for Image Retrieval
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Detection with Automatic Scale Selection
International Journal of Computer Vision
Recognition without Correspondence using MultidimensionalReceptive Field Histograms
International Journal of Computer Vision
Training Support Vector Machines: an Application to Face Detection
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Robust Face Tracking Using Color
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Recursive Gaussian Derivative Filters
ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Object Recognition from Local Scale-Invariant Features
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Trademark matching and retrieval in sports video databases
Proceedings of the international workshop on Workshop on multimedia information retrieval
Predictive visual context in object detection
CONTEXT'03 Proceedings of the 4th international and interdisciplinary conference on Modeling and using context
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In this article, we describe a module for the identification of brand logos from video data. A model for the visual appearance of each logo is generated from a small number of sample images using multi-dimensional histograms of scale-normalised chromatic Gaussian receptive fields. We compare several state-of-the-art identification techniques, based multi-dimensional histograms. Each of the methods display high recognition rates and can be used for logo identification. Our method for calculating scale normalized Gaussian receptive fields has linear computational complexity, and is thus well adapted to a real time system. However, with the current generation of microprocessors we obtain at best only 2 images per second when processing a full PAL video stream. To accelerate the process, we propose an architecture that applies color based logo detection to initiate a robust tracking process. Tracked logos are then identified off line using receptive field histograms. The resulting real time system is evaluated using video streams from sports Formula-1 races and football.