Name
Title | ||
|---|---|---|
Compact: Biometric Dataset Of Face Images Acquired In Uncontrolled Indoor Environment |
Abstract | ||
|---|---|---|
Biometric databases are important components that help improve the performance of state-of-the-art recognition applications. The availability of more and more challenging data is attracting the attention of researchers, who are systematically developing novel recognition algorithms and increasing the accuracy of identification. Surprisingly, most of the popular face datasets (like LFW or IJBA) are not fully unconstrained. The majority of the available images were not acquired on-the-move, which reduces the amount of blurring that is caused by motion or incorrect focusing. Therefore, the COMPACT database for studying less-cooperative face recognition is introduced in this paper. The dataset consists of high-resolution images of 108 subjects acquired in a fully automated manner as people go through the recognition gate. This ensures that the collected data contains real-world degradation factors: different distances, expressions, occlusions, pose variations, and motion blur. Additionally, the authors conducted a series of experiments that verified the face-recognition performance on the collected data. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.7494/csci.2019.20.1.3020 | COMPUTER SCIENCE-AGH |
Keywords | Field | DocType |
biometrics, face recognition, face database, less-cooperative identification | Facial recognition system,Computer vision,Expression (mathematics),Computer science,Motion blur,Artificial intelligence,Recognition algorithm,Biometrics,Machine learning | Journal |
Volume | Issue | ISSN |
20 | 1 | 1508-2806 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wlodarczyk, M. | 1 | 6 | 3.71 |
| Kacperski, D. | 2 | 4 | 2.85 |
| W. Sankowski | 3 | 62 | 4.11 |
| Kamil Grabowski | 4 | 40 | 2.22 |