Making large-scale support vector machine learning practical
Advances in kernel methods
Multiple view geometry in computer vision
Multiple view geometry in computer vision
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Blobworld: Image Segmentation Using Expectation-Maximization and Its Application to Image Querying
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust analysis of feature spaces: color image segmentation
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Segmentation and Analysis of Leg Ulcers Color Images
MIAR '01 Proceedings of the International Workshop on Medical Imaging and Augmented Reality (MIAR '01)
Case-Based Tissue Classification for Monitoring Leg Ulcer Healing
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
Accurate 3d structure measurements from two uncalibrated views
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
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Region classification from a single image is no more reliable when the labeling must be applied on a 3D surface. Depending on camera viewpoint and surface curvature, lighting variations and perspective effects alter colorimetric analysis and area measurements. This problem can be overcome if a 3D model of the object of interest is available. This general approach has been evaluated for the design of a complete wound assessment tool using a simple free handled digital camera. Clinical tests demonstrate that multi view classification results in enhanced tissue labeling and more precise measurements, a significant step toward accurate monitoring of the healing process.