Name
Abstract | ||
|---|---|---|
Video-based object recognition faces the problem of multi-view object variance, noisy conditions, and limited computational resources. In our previous work, we introduced a multi-view recognition approach with a compact global image descriptor coupled with orientation sensor data. Since our purpose is to run all computations in a handheld device, contrary to more intensive deep learning approaches, now we investigate the efficiency of our approach using a full representation image model with KD-Tree indexing. Experimental results show the effectiveness of our approach through three databases using noisy images. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IWSSIP.2016.7502714 | 2016 International Conference on Systems, Signals and Image Processing (IWSSIP) |
Keywords | Field | DocType |
object recognition,view centered recognition,orientation sensor,image retrieval,KD-Tree | Computer vision,3D single-object recognition,Pattern recognition,Computer science,Search engine indexing,Mobile device,Artificial intelligence,Deep learning,Gaussian noise,Cognitive neuroscience of visual object recognition,Computation | Conference |
ISSN | Citations | PageRank |
2157-8672 | 0 | 0.34 |
References | Authors | |
4 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| László Czuni | 1 | 68 | 13.41 |
| metwally rashad | 2 | 4 | 2.15 |