Name
Abstract | ||
|---|---|---|
This paper proposes a novel calculation method of personality based on Chinese physiognomy. The proposed solution combines ancient and modern physiognomy to understand the relationship between personality and facial features and to model a baseline to shape facial features. We compute a histogram of image by searching for threshold values to create a binary image in an adaptive way. The two-pass connected component method indicates the feature's region. We encode the binary image to remove the noise point, so that the new connected image can provide a better result. According to our analysis of contours, we can locate facial features and classify them by means of a calculation method. The number of clusters is decided by a model and the facial feature contours are classified by using the k-means method. The validity of our method was tested on a face database and demonstrated by a comparative experiment. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.jvlc.2017.09.006 | Journal of Visual Languages & Computing |
Field | DocType | Volume |
Histogram,Computer vision,ENCODE,Pattern recognition,Computer science,Binary image,Feature extraction,Connected component,Physiognomy,Artificial intelligence | Journal | 43 |
Issue | ISSN | Citations |
C | 1045-926X | 2 |
PageRank | References | Authors |
0.43 | 6 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yujie Liu | 1 | 2 | 0.43 |
| Mao Lin Huang | 2 | 736 | 80.10 |
| Weidong Huang | 3 | 131 | 19.13 |
| Jie Liang | 4 | 86 | 10.85 |