An LBP cascade can be trained to perform similarly (or better) than the Haar cascade, but out of the box, the Haar cascade is about 3x slower, and depending on your data, about 1-2% better at accurately detecting the location of a face. This increase in accuracy is quite significant given that face detection can operate in the 95%+ accuracy range.
Below are some results when using the MUCT dataset.
A correct detection is noted when there is at least a 50% overlap between the ground-truth and OpenCV detected coordinates.
Cascade:haarcascade_frontalface_alt2.xml
Datafile:muct.csv
|---------------------------------------------------|
| Hits | Misses | False Detects | Multi-hit |
| 3635 | 55 | 63 | 5 |
|---------------------------------------------------|
Time:4m2.060s
vs:
Cascade:lbpcascade_frontalface.xml
Datafile:muct.csv
|---------------------------------------------------|
| Hits | Misses | False Detects | Multi-hit |
| 3569 | 106 | 77 | 3 |
|---------------------------------------------------|
Time:1m12.511s
