Principles of interactive computer graphics (2nd ed.)
Principles of interactive computer graphics (2nd ed.)
Representation of Three-Dimensional Digital Images
ACM Computing Surveys (CSUR)
Representations for space planning
Communications of the ACM
Efficient computation and data structures for graphics.
Efficient computation and data structures for graphics.
Data structures for quadtree approximation and compression
Communications of the ACM
Efficient Component Labeling of Images of Arbitrary Dimension Represented by Linear Bintrees
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model Construction and Shape Recognition from Occluding Contours
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient ray tracing of volume data
ACM Transactions on Graphics (TOG)
Octrees for faster isosurface generation
ACM Transactions on Graphics (TOG)
SCG '85 Proceedings of the first annual symposium on Computational geometry
SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
Hierarchical Data Structures and Algorithms for Computer Graphics
IEEE Computer Graphics and Applications
Efficient octree conversion by connectivity labeling
SIGGRAPH '84 Proceedings of the 11th annual conference on Computer graphics and interactive techniques
Reconstructing animated meshes from time-varying point clouds
SGP '08 Proceedings of the Symposium on Geometry Processing
3D elbow kinematics with monoplanar fluoroscopy: in silico evaluation
EURASIP Journal on Advances in Signal Processing - Image processing and analysis in biomechanics
Parallel volume rendering with early ray termination for visualizing large-scale datasets
ISPA'04 Proceedings of the Second international conference on Parallel and Distributed Processing and Applications
Proceedings of the Digital Production Symposium
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A tree data structure for representing multidimensional digital binary images is described. The method is based on recursive subdivision of the d-dimensional space into 2d hyperoctants. An algorithm for constructing the tree of a d-dimensional binary image from the trees of its (d - 1 )-dimensional cross sections is given. The computational advantages of the data structure and the algorithm are demonstrated both theoretically and in application to a three-dimensional reconstruction of a human brain.