This document summarizes a student's research project on real-time face detection, tracking, and attribute recognition. The goal is to develop a system that can detect faces in real-time and identify attributes like gender, race, etc. It will apply techniques like the Viola-Jones face detection framework, L1 minimization tracking, and face attribute recognition. Potential applications include surveillance, security, human-computer interaction, robotics, and more. The document outlines the methods used and references related work.

1. Real-time face detection, tracking and attributes
Danyang Wang
Mentor: Jia-Bin Huang
Department of electrical and computer engineering
University of Illinois, Urbana-Champaign
Goal Applications
• Achieve real-time face detection and tracking with  Surveillance  Security
the ability of telling attributes of faces(e.g. gender,  Human-computer interactions  Robotics
 Softwares  And more!
race, etc)
Dutch, Male
Methods
Chinese, Male Korean, Male
 Face detection (viola-jones framework) [1]
 Object tracking (L1 minimization tracking) [2]
http://news.duowan.com/10356/warcraft.jpg http://www.merl.com/areas/images/FaceDetection.jpg
 Face attributes [3]
Face detection
1. Integral Image algorithm [1] 2. Haar-like features and classifiers [1]
Lienhart introduced features [1]
Sample features 3. Cascade [1]
Object Tracking [2] Face attributes [3]
References
[1] Viola and Jones. Robust Real-time Object Detection, ICPV. 2001.
P.U.R.E Research Symposium [2] Mei and Ling. Robust Visual Tracking using L1 Minimization, ICCV. 2009.
[3] Kumar et al. Attribute and Simile Classifiers for Face Verification, ICCV.
2009.