Empirical Performance Evaluation of Graphics Recognition Systems
IEEE Transactions on Pattern Analysis and Machine Intelligence
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Object count/area graphs for the evaluation of object detection and segmentation algorithms
International Journal on Document Analysis and Recognition
Scale-invariant shape features for recognition of object categories
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Detecting moving objects, ghosts, and shadows in video streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
Parametrization of an image understanding quality metric with a subjective evaluation
Pattern Recognition Letters
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We propose in this paper a new evaluation metric that enables to quantify the quality of an image interpretation result. This metric takes into account the a priori knowledge used by the interpretation algorithm and the ground truth associated with the original image. We combine two metrics that evaluate the localization and recognition results of each detected object. We show that the proposed metric fulfills some theoretical properties and has a correct behavior face to empirical experiments on an image benchmark database. We think that this metric could be a reliable reference for image and video understanding competitions.