Name
Abstract | ||
|---|---|---|
Local feature descriptors play an important role in facial expression recognition. Local Binary Pattern (LBP) only considers the signal information of the difference between the gray value of the center pixel and the neighbor pixel. It does not take the magnitude information into consideration and has poor robustness. Local Mapped Pattern (LMP) is not ideal for discriminating differences between different textures and experimental result is not excellent. This paper proposes a novel feature descriptor based on gray-level difference mapping, called Local Double Binary Mapped Pattern (LDBMP). This new approach is an improvement over the previous LBP and LMP, not only retains the advantages of LBP and LMP but also preserves the information of magnitude and captures nuances that occur in the image. In our experiments, the new descriptor performs favorably. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1007/978-3-030-00767-6_45 | ADVANCES IN MULTIMEDIA INFORMATION PROCESSING - PCM 2018, PT II |
Keywords | Field | DocType |
Local double binary mapped pattern,Feature fusion,Facial expression recognition | Computer vision,Feature fusion,Feature descriptor,Facial expression recognition,Pattern recognition,Computer science,Local binary patterns,Robustness (computer science),Pixel,Artificial intelligence,Binary number | Conference |
Volume | ISSN | Citations |
11165 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 13 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Chunjian Yang | 1 | 0 | 0.34 |
| Min Hu | 2 | 31 | 12.64 |
| Yaqin Zheng | 3 | 0 | 0.34 |
| Xiaohua Wang | 4 | 1 | 2.12 |
| Yong Gao | 5 | 8 | 2.16 |
| Hao Wu | 6 | 92 | 38.83 |