Large-scale Image Retrieval using Neural Net Descriptors
| Authors | |
|---|---|
| Year of publication | 2015 |
| Type | Article in Proceedings |
| Conference | Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval |
| MU Faculty or unit | |
| Citation | |
| Web | ACM Portal |
| Doi | http://dx.doi.org/10.1145/2766462.2767868 |
| Field | Informatics |
| Keywords | metric indexing; deep convolutional neural network; contentbased image retrieval; k-NN search |
| Description | One of current big challenges in computer science is development of data management and retrieval techniques that would keep pace with the evolution of contemporary data and with the growing expectations on data processing. Various digital images became a common part of both public and enterprise data collections and there is a natural requirement that the retrieval should consider more the actual visual content of the image data. In our demonstration, we aim at the task of retrieving images that are visually and semantically similar to a given example image; the system should be able to online evaluate k nearest neighbor queries within a collection containing tens of millions of images. The applicability of such a system would be, for instance, on stock photography sites, in e-shops searching in product photos, or in collections from a constrained Web image search. |
| Related projects: |