Fast face detection and localization from multi-views using statistical approach

Window-based face detection methods are fast. However their results are coarse, pose dependent and require fine face alignment for face analysis. Recently a statistical approach is introduced by Toews and Arbel [1], which is able to detect faces in multiple poses and does not require face alignment....

Full description

Saved in:
Bibliographic Details
Main Authors: Teoh, Eam Khwang, Anvar, Seyed Mohammad Hassan, Yau, Wei-Yun
Other Authors: School of Electrical and Electronic Engineering
Format: Conference or Workshop Item
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/100453
http://hdl.handle.net/10220/17901
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
Description
Summary:Window-based face detection methods are fast. However their results are coarse, pose dependent and require fine face alignment for face analysis. Recently a statistical approach is introduced by Toews and Arbel [1], which is able to detect faces in multiple poses and does not require face alignment. However, their method is slow compared to the window-based method. In this paper, we proposed a method, which capable of detecting faces in multiple poses in near real time and also does not require face alignment. Experimental results show that our proposed method has comparable accuracy with the Toews and Arbel’s method but has significantly lower processing time.