Abstract
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.
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Wannous, H., Lucas, Y., Treuillet, S., Albouy, B. (2008). Fusion of Multi-view Tissue Classification Based on Wound 3D Model. In: Blanc-Talon, J., Bourennane, S., Philips, W., Popescu, D., Scheunders, P. (eds) Advanced Concepts for Intelligent Vision Systems. ACIVS 2008. Lecture Notes in Computer Science, vol 5259. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88458-3_84
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DOI: https://doi.org/10.1007/978-3-540-88458-3_84
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