A comprehensive physical model for light reflection
Proceedings of the 18th annual conference on Computer graphics and interactive techniques
Differential algorithm for the determination of shape from shading using a point light source
Image and Vision Computing
Alignment by Maximization of Mutual Information
International Journal of Computer Vision
Deformable models for laparoscopic surgery simulation
COMPUGRAPHICS '96 Proceedings of the fifth international conference on computational graphics and visualization techniques on Visualization and graphics on the World Wide Web
Reflectance and texture of real-world surfaces
ACM Transactions on Graphics (TOG)
Inverse global illumination: recovering reflectance models of real scenes from photographs
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
A Flexible New Technique for Camera Calibration
IEEE Transactions on Pattern Analysis and Machine Intelligence
Image-based rendering of diffuse, specular and glossy surfaces from a single image
Proceedings of the 28th annual conference on Computer graphics and interactive techniques
Least squares conformal maps for automatic texture atlas generation
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
Image-based reconstruction of spatial appearance and geometric detail
ACM Transactions on Graphics (TOG)
A new point matching algorithm for non-rigid registration
Computer Vision and Image Understanding - Special issue on nonrigid image registration
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
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Photo-realistic rendering combined with vision techniques is an important trend in developing next generation surgical simulation devices. Training with simulator is generally low in cost and more efficient than traditional methods that involve supervised learning on actual patients. Incorporating genuine patient data in the simulation can significantly improve the efficacy of training and skills assessment. In this paper, a photo-realistic simulation architecture is described that utilises patient-specific models for training in minimally invasive surgery. The datasets are constructed by combining computer tomographic images with bronchoscopy video of the same patient so that the three dimensional structures and visual appearance are accurately matched. Using simulators enriched by a library of datasets with sufficient patient variability, trainees can experience a wide range of realistic scenarios, including rare pathologies, with correct visual information. In this paper, the matching of CT and video data is accomplished by using a newly developed 2D/3D registration method that exploits a shape from shading similarity measure. Additionally, a method has been devised to allow shading parameter estimation by modelling the bidirectional reflectance distribution function (BRDF) of the visible surfaces. The derived BRDF is then used to predict the expected shading intensity such that a texture map independent of lighting conditions can be extracted. Thus new views can be generated that were not captured in the original bronchoscopy video, thus allowing free navigation of the acquired 3D model with enhanced photo-realism.