Anuj Srivastava was the invited talker for the keynote address. The slides of his talk "Statistical Analysis of Shapes of 3D Objects for Retrieval, Recognition and Classification" are available online [PDF].
Background and Motivations
The use of three-dimensional (3D) image and model databases throughout the Internet is growing both in number and size. The development of modeling tools, 3D scanners, 3D graphic accelerated hardware, Web3D, and so on, is enabling access to 3D materials of high quality.
The emergence of 3D media is also directly related to the emergence of the 3D acquisition technologies. Indeed, recent advances in 3D scanner acquisition and 3D graphics rendering technologies boost the creation of 3D model archives for several application domains. These include archeology, cultural heritage, computer-assisted design (CAD), medicine, 3D face recognition, videogames or bioinformatics. Thereupon, the development of efficient search mechanisms is required for the effective retrieval of 3D objects from large repositories.
The purpose of this workshop is to bring together researchers interested in 3D retrieval from different fields (computer vision, computer graphics, machine learning and human-computer interaction). Its goal is to provide a state-of-the-art overview of challenges in the research on 3D retrieval. This workshop seeks original high innovative research in the area of 3D retrieval.
The workshop will be held October 25, 2010, in conjunction with ACM Multimedia 2010 (25-29 October 2010, Firenze, Italy).
The workshop opens a call for papers to attract a representative number of papers from leading researchers working on topics related to 3D object retrieval and applications, including but not limited to:
- 3D object similarity and matching
- 3D Object classification, indexing, and mining
- Similarity of nonrigid objects
- Feature extraction, model decomposition and segmentation
- Partial and many-to-many matching
- Bag-of-features approaches to 3D retrieval
- Matching under uncertainty and noise
- Query interfaces and search modalities
- Multi-level representations for matching and retrieval
- Semantics-driven 3D object retrieval and classification
- Sketch-based retrieval
- Benchmarking issues
- Relevance feedback methods
- Active learning
- Generative / Discriminative approaches in 3D object categorization
- 2D/3D retrieval
- 3D motion retrieval