An Adaptive Contour Closure Algorithm and Its Experimental Evaluation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance characterisation in computer vision: statistics in testing and design
Imaging and vision systems
Order Parameters for Detecting Target Curves in Images: When Does High Level Knowledge Help?
International Journal of Computer Vision - Special issue on statistical and computational theories of vision: Part II
Statistical Edge Detection: Learning and Evaluating Edge Cues
IEEE Transactions on Pattern Analysis and Machine Intelligence
On Performance Characterization and Optimization for Image Retrieval
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
Valmet: A New Validation Tool for Assessing and Improving 3D Object Segmentation
MICCAI '01 Proceedings of the 4th International Conference on Medical Image Computing and Computer-Assisted Intervention
Perceptual Grouping by Selection of a Logically Minimal Model
International Journal of Computer Vision
Evaluation of global image thresholding for change detection
Pattern Recognition Letters
Nonrigid image registration: guest editors' introduction
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Recognizing faces with PCA and ICA
Computer Vision and Image Understanding - Special issue on Face recognition
Random Sampling for Subspace Face Recognition
International Journal of Computer Vision
Performance evaluation and optimization for content-based image retrieval
Pattern Recognition
The Bayes Decision Rule Induced Similarity Measures
IEEE Transactions on Pattern Analysis and Machine Intelligence
Localized versus locality-preserving subspace projections for face recognition
Journal on Image and Video Processing
Spatio-temporal background models for outdoor surveillance
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Performance characterization in computer vision: A guide to best practices
Computer Vision and Image Understanding
Image segmentation evaluation: A survey of unsupervised methods
Computer Vision and Image Understanding
International Journal of Business Intelligence and Data Mining
Combining invariance, robustness, and stability in computer vision
CGIM '08 Proceedings of the Tenth IASTED International Conference on Computer Graphics and Imaging
Hand-drawn face sketch recognition by humans and a PCA-based algorithm for forensic applications
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
The performance of various edge detector algorithms in the analysis of total hip replacement x-rays
CIARP'05 Proceedings of the 10th Iberoamerican Congress conference on Progress in Pattern Recognition, Image Analysis and Applications
Modeling, evaluation and control of a road image processing chain
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Image segmentation using fuzzy logic, neural networks and genetic algorithms: survey and trends
Machine Graphics & Vision International Journal
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
Linear reconstruction measure steered nearest neighbor classification framework
Pattern Recognition
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From the Publisher:Empirical Evaluation Techniques in Computer Vision presents methods that allow comparative assessment of algorithms and the accompanying benefits: places computer vision on solid experimental and scientific grounds, assists the development of engineering solutions to practical problems, allows accurate assessments of computer vision research, provides convincing evidence that computer vision research results in practical solutions. The chapters in this volume cover the three main paradigms for evaluating computer vision algorithms. The paradigms are: (1) evaluations that are independently administered, (2) evaluation of a set of algorithms by one research group, and (3) evaluation methods that feature ground truthing procedures as a major component.