Name
Abstract | ||
|---|---|---|
The paper reports a novel cloud based approach for image matching between high-resolution images of faces and low resolution images of ID Cards. We design our application matching the mobile cloud computing design guidelines with the use of CUDA kernel invocation from regular mobile devices (devices that naively don't support CUDA GPGPUs) as a novel contribution. Face matching is performed by the OpenFace deep neural network, which evaluates pre-processed images in cloud, whilst pre-processing is done on mobile device. To test our system, we built an image dataset of 30 subject caputeres in 10 different poses, denoised to reduce any traces of stamps or watermark on the ID cards, mixed to the well known ORL and LFW datasets. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-70742-6_35 | Lecture Notes in Computer Science |
Keywords | Field | DocType |
Cloud computing,Neural network,Deep learning,Face matching | Mobile cloud computing,Kernel (linear algebra),Computer vision,Computer science,CUDA,Watermark,Mobile device,Artificial intelligence,Deep learning,Artificial neural network,Cloud computing | Conference |
Volume | ISSN | Citations |
10590 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 5 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Raffaele Montella | 1 | 210 | 23.13 |
| Alfredo Petrosino | 2 | 1314 | 83.52 |
| Vincenzo Santopietro | 3 | 1 | 1.03 |