Sciweavers

Share
PAMI
2007

High-Performance Rotation Invariant Multiview Face Detection

8 years 8 months ago
High-Performance Rotation Invariant Multiview Face Detection
Abstract—Rotation invariant multiview face detection (MVFD) aims to detect faces with arbitrary rotation-in-plane (RIP) and rotationoff-plane (ROP) angles in still images or video sequences. MVFD is crucial as the first step in automatic face processing for general applications since face images are seldom upright and frontal unless they are taken cooperatively. In this paper, we propose a series of innovative methods to construct a high-performance rotation invariant multiview face detector, including the Width-First-Search (WFS) tree detector structure, the Vector Boosting algorithm for learning vector-output strong classifiers, the domain-partition-based weak learning method, the sparse feature in granular space, and the heuristic search for sparse feature selection. As a result of that, our multiview face detector achieves low computational complexity, broad detection scope, and high detection accuracy on both standard testing sets and real-life images.
Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao
Added 27 Dec 2010
Updated 27 Dec 2010
Type Journal
Year 2007
Where PAMI
Authors Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao
Comments (0)
books