Name
Abstract | ||
|---|---|---|
Glasses detection plays an important role in face recognition and soft biometrices for person identification. However, automatic glasses detection is still a challenging problem under real application scenarios, because face variations, light conditions, and self-occlusion, have significant influence on its performance. Inspired by the success of Deep Convolutional Neural Networks (DCNN) on face recognition, object detection and image classification, we propose a glasses detection method based on DCNN. Specifically, we devise a Glasses Network (GNet), and pre-train it as a face identification network with a large number of face images. The pre-trained GNet is finally fine-tuned as a glasses detection network by using another set of facial images wearing and not wearing glasses. Evaluation experiments have been done on two public databases, Multi-PIE and LFW. The results demonstrate the superior performance of the proposed method over competing methods. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1007/978-3-319-46654-5_78 | BIOMETRIC RECOGNITION |
Keywords | Field | DocType |
Glasses detection,Deep convolutional neural network,GNet,Deep learning | Object detection,Facial recognition system,Pattern recognition,Computer science,Convolutional neural network,Artificial intelligence,Deep learning,Contextual image classification,Machine learning | Conference |
Volume | ISSN | Citations |
9967 | 0302-9743 | 1 |
PageRank | References | Authors |
0.37 | 15 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Shao | 1 | 1 | 0.37 |
| Ronghang Zhu | 2 | 3 | 0.73 |
| Qijun Zhao | 3 | 419 | 38.37 |