Performance evaluation in visual surveillance using the F-measure
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
Image segmentation evaluation: A survey of unsupervised methods
Computer Vision and Image Understanding
An object-based comparative methodology for motion detection based on the F-Measure
Computer Vision and Image Understanding
Performance evaluation of image segmentation
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
Rough sets and neural networks based aerial images segmentation method
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part IV
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To be reliable, an automatic segmentation evaluation metric has to be validated by subjective tests.In this paper, a formal protocol for subjective tests for segmentation quality assessment is presented.The most common artifacts produced by segmentation algorithms are identified and an extensive analysis of their effects on the perceived quality is performed.A psychophysical experiment was performed to assess the quality of video with segmentation errors.The results show how an objective segmentation evaluation metric can be defined as a function of various error types.