3D face detection based on salient features extraction and skin colour detection using data mining. (3rd October 2017)

• Record Type: Journal Article
• Authors: El Sayed, Abdul Rahman; El Chakik, Abdallah; Alabboud, Hassan; Yassine, Adnan
• Is Part Of: Imaging science journal. Volume 65:Number 7(2017)
• Page Start: 393
• Page End: 408
• Publication Date: 2017-10-03
• Subjects: 3D facial point clouds detection -- 3D point clouds saliency -- 3D point clouds segmentation -- classification -- 3D object processing -- points clouds; Imaging systems -- Periodicals; 621.36705
• DOI: 10.1080/13682199.2017.1358528
• Languages: English
• ISSNs: 1368-2199

Abstract

ABSTRACT: Face detection has an essential role in many applications. In this paper, we propose an efficient and robust method for face detection on a 3D point cloud represented by a weighted graph. This method classifies graph vertices as skin and non-skin regions based on a data mining predictive model. Then, the saliency degree of vertices is computed to identify the possible candidate face features. Finally, the matching between non-skin regions representing eyes, mouth and eyebrows and salient regions is done by detecting collisions between polytopes, representing these two regions. This method extracts faces from situations where pose variation and change of expressions can be found. The robustness is showed through different experimental results. Moreover, we study the stability of our method according to noise. Furthermore, we show that our method deals with 2D images.