The goal of visualization is the accurate, interactive, and intuitive presentation of data. Complex numerical simulations, high-resolution imaging devices and incre- ingly common environment-embedded sensors are the primary generators of m- sive data sets. Being able to derive scienti?c insight from data increasingly depends on having mathematical and perceptual models to provide the necessary foundation for effective data analysis and comprehension. The peer-reviewed state-of-the-art research papers included in this book focus on continuous data models, such as is common in medical imaging or computational modeling. From the viewpoint of a visualization scientist, we typically collaborate with an application scientist or engineer who needs to visually explore or study an object which is given by a set of sample points, which originally may or may not have been connected by a mesh. At some point, one generally employs low-order piecewise polynomial approximationsof an object, using one or several dependent functions. In order to have an understanding of a higher-dimensional geometrical "object" or function, ef?cient algorithms supporting real-time analysis and manipulation (- tation, zooming) are needed. Often, the data represents 3D or even time-varying 3D phenomena (such as medical data), and the access to different layers (slices) and structures (the underlying topology) comprising such data is needed.

The goal of visualization is the accurate, interactive, and intuitive presentation of data. Complex numerical simulations, high-resolution imaging devices and incre- ingly common environment-embedded sensors are the primary generators of m- sive data sets. Being able to derive scienti?c insight from data increasingly depends on having mathematical and perceptual models to provide the necessary foundation for effective data analysis and comprehension. The peer-reviewed state-of-the-art research papers included in this book focus on continuous data models, such as is common in medical imaging or computational modeling. From the viewpoint of a visualization scientist, we typically collaborate with an application scientist or engineer who needs to visually explore or study an object which is given by a set of sample points, which originally may or may not have been connected by a mesh. At some point, one generally employs low-order piecewise polynomial approximationsof an object, using one or several dependent functions. In order to have an understanding of a higher-dimensional geometrical "object" or function, ef?cient algorithms supporting real-time analysis and manipulation (- tation, zooming) are needed. Often, the data represents 3D or even time-varying 3D phenomena (such as medical data), and the access to different layers (slices) and structures (the underlying topology) comprising such data is needed.

The two volume set LNCS 4841 and LNCS 4842 constitutes the refereed proceedings of the Third International Symposium on Visual Computing, ISVC 2007, held in Lake Tahoe, NV, USA in November 2007.

The 77 revised full papers and 42 poster papers presented together with 32 full and 5 poster papers of 6 special tracks were carefully reviewed and selected from more than 270 submissions. The papers cover the four main areas of visual computing: vision, graphics, visualization, and virtual reality. There 6 additional special tracks address issues such as intelligent algorithms for smart monitoring of complex environments, object recognition, image databases, algorithms for the understanding of dynamics in complex and cluttered scenes, medical data analysis, and soft computing in image processing. The papers of this volume are organized in topical sections on motion and tracking, segmentation, feature extraction, classification, intelligent algorithms for smart monitoring of shape/recognition, image databases, soft computing in image processing, and posters.

The two volume set LNCS 4841 and LNCS 4842 constitutes the refereed proceedings of the Third International Symposium on Visual Computing, ISVC 2007, held in Lake Tahoe, NV, USA in November 2007.

The 77 revised full papers and 42 poster papers presented together with 32 full and 5 poster papers of 6 special tracks were carefully reviewed and selected from more than 270 submissions. The papers cover the four main areas of visual computing: vision, graphics, visualization, and virtual reality. There 6 additional special tracks address issues such as intelligent algorithms for smart monitoring of complex environments, object recognition, image databases, algorithms for the understanding of dynamics in complex and cluttered scenes, medical data analysis, and soft computing in image processing. The papers of this volume are organized in topical sections on motion and tracking, computer graphics, virtual reality, medical data analysis, calibration/reconstruction, visualization, computer vision applications, algorithms for the understanding, face reconstruction and processing, object recognition, and shape/motion/tracking.