Learning to Localize Objects with Structured Output Regression
ECCV '08 Proceedings of the 10th European Conference on Computer Vision: Part I
Branch and bound strategies for non-maximal suppression in object detection
EMMCVPR'11 Proceedings of the 8th international conference on Energy minimization methods in computer vision and pattern recognition
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This paper deals with a comparative study of metrics allowing the evaluation of results provided by object localization algorithms. We particulary focus on localization by the bounding box representation. 26 metrics are studied in this paper. A protocol is presented for the creation of ground truths and synthetic results of localization algorithms. These synthetic results permit to simulate several inaccuracies (translation, scale errors. . . ) and to study the metrics behaviors face to the considered alterations. Finally, some conclusions and perspectives are given.