Efficient RANSAC for Point‐Cloud Shape Detection
An automatic algorithm to detect basic shapes in unorganized point clouds based on random sampling and detects planes, spheres, cylinders, cones and tori, and obtains a representation solely consisting of shape proxies.
Octree-based Point-Cloud Compression
A progressive compression method for point sampled models that is specifically apt at dealing with densely sampled surface geometry and it is demonstrated that additional point attributes, such as color, can be well integrated and efficiently encoded in this framework.
3D zernike descriptors for content based shape retrieval
- Marcin Novotni, R. Klein
- Computer ScienceACM Symposium on Solid Modeling and Applications
- 16 June 2003
This paper advocates the usage of so-called 3D Zernike invariants as descriptors for content based 3D shape retrieval and provides practical analysis of these invariants along with algorithms and computational details.
Automatic reconstruction of parametric building models from indoor point clouds
Simple and efficient compression of animation sequences
A new geometry compression method for animations, which is based on the clustered principal component analysis (CPCA), which outperforms other compression schemes like pure PCA based compression or combinations with linear prediction coding, while maintaining a better reconstruction error.
Shape retrieval using 3D Zernike descriptors
Efficient and Realistic Visualization of Cloth
A novel interactive rendering algorithm to preserve this "look and feel" of different fabrics by using the bidirectional texture function of the fabric, which is acquired from a rectangular probe and after synthesis, mapped onto the simulated geometry.
3D Shape Matching with 3D Shape Contexts
This paper introduces an enhanced 3D approach of the recently introduced 2D Shape Contexts that can be used for measuring 3d shape similarity as fast, intuitive and powerful similarity model for 3D objects.
Automatic reconstruction of fully volumetric 3D building models from oriented point clouds