Generating octree models of 3D objects from their silhouettes in a sequence of images
Computer Vision, Graphics, and Image Processing
Algorithms for Graphics and Imag
Algorithms for Graphics and Imag
Computational geometry.
Multiresolution, incremental generation of 3D computer models from video data
SMA '93 Proceedings on the second ACM symposium on Solid modeling and applications
How Far 3D Shapes Can Be Understood from 2D Silhouettes
IEEE Transactions on Pattern Analysis and Machine Intelligence
Efficient geometry-based similarity search of 3D spatial databases
SIGMOD '99 Proceedings of the 1999 ACM SIGMOD international conference on Management of data
Symmetry Identification of a 3-D Object Represented by Octree
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Visual Hull Concept for Silhouette-Based Image Understanding
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape-From-Silhouette Across Time Part I: Theory and Algorithms
International Journal of Computer Vision
What's NEXT? An interactive next best view approach
Pattern Recognition
Surface model reconstruction of 3D objects from multiple views
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Occluded 3d object recognition using partial shape and octree model
ICIC'05 Proceedings of the 2005 international conference on Advances in Intelligent Computing - Volume Part I
| Hi-index | 0.14 |
A fast, efficient, algorithm that processes polyhedral cones from views of an object to produce an octree representation of the object is proposed. A polyhedral cone defined by both a viewpoint and a polygonal contour of the object in the image for each view always contains the object. Thus the common region of the cones for multiple views is considered to be an approximating one of the object. The octree representation controls all cubic regions in three-dimensional space as a set of nodes with a hierarchical description in positioning, and therefore is suitable for registration of the common region. The computational complexity of the algorithm is directly proportional to the common region surface area and exponentially proportional to the finest resolution level of the octree. The calculation time of the algorithm is determined for illustrative examples of three-dimensional objects.