Name
Abstract | ||
|---|---|---|
•We present a novel view-based 3D object retrieval framework, which is deployed over a graph-based collaborative learning scheme to intelligently fuse multiple features.•The hypergraph based collaborative feature learning scheme to fuse complement descriptors from both the contour and the interior region of 3D object effectively.•The view-based 3D object retrieval is done via a greedy bipartite graph matching algorithm, which achieves highly accurate and efficient 3D object matching.•The interactive learning procedure with user feedbacks achieved better performance. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.jvcir.2018.11.046 | Journal of Visual Communication and Image Representation |
Keywords | Field | DocType |
3D Object retrieval,Collaborative feature learning,Hypergraph learning,Bipartite graph matching | Graph,Collaborative learning,Pattern recognition,Hypergraph,Theoretical computer science,Concatenation,Artificial intelligence,Object matching,Fuse (electrical),Mathematics,Feature learning,Performance improvement | Journal |
Volume | ISSN | Citations |
58 | 1047-3203 | 0 |
PageRank | References | Authors |
0.34 | 23 | 3 |