The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Download
Publications Copernicus
Download
Citation
Articles | Volume XLII-2/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W4, 237–241, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W4-237-2017
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W4, 237–241, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W4-237-2017

  10 May 2017

10 May 2017

ENHANCEMENT OF FAST FACE DETECTION ALGORITHM BASED ON A CASCADE OF DECISION TREES

V. V. Khryashchev, A. A. Lebedev, and A. L. Priorov V. V. Khryashchev et al.
  • YSU, Yaroslavl, Russia

Keywords: Face Detection, Cascade Algorithm, Decision Trees

Abstract. Face detection algorithm based on a cascade of ensembles of decision trees (CEDT) is presented. The new approach allows detecting faces other than the front position through the use of multiple classifiers. Each classifier is trained for a specific range of angles of the rotation head. The results showed a high rate of productivity for CEDT on images with standard size. The algorithm increases the area under the ROC-curve of 13% compared to a standard Viola-Jones face detection algorithm. Final realization of given algorithm consist of 5 different cascades for frontal/non-frontal faces. One more thing which we take from the simulation results is a low computational complexity of CEDT algorithm in comparison with standard Viola-Jones approach. This could prove important in the embedded system and mobile device industries because it can reduce the cost of hardware and make battery life longer.