Name
Title | ||
|---|---|---|
A Computer Vision System for Analyzing and Interpreting the Cephalo-ocular Behavior of Drivers in a Simulated Driving Context |
Abstract | ||
|---|---|---|
In this paper we introduce a new computer vision framework for the analysis and interpretation of the cephalo-ocular behavior of drivers. We start by detecting the most important facial features, namely the nose tip and the eyes. For that, we introduce a new algorithm for eyes detection and we call upon the cascade of boosted classifiers technique based on Haar-like features for detecting the nose tip. Once those facial features are well identified, we apply the pyramidal Lucas-Kanade method for tracking purposes. Events resulting from those two approaches are combined in order to identify, analyze and interpret the cephalo-ocular behavior of drivers. Experimental results confirm both the robustness and the effectiveness of the proposed framework. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/CRV.2010.35 | Computer and Robot Vision |
Keywords | Field | DocType |
haar-like feature,nose tip,cephalo-ocular behavior,new algorithm,simulated driving context,new computer vision framework,proposed framework,important facial feature,computer vision system,classifiers technique,facial feature,eyes detection,lucas kanade,face,face recognition,haar like features,shape,computer vision,pixel,tracking | Facial recognition system,Computer vision,Pattern recognition,Computer science,Haar-like features,Robustness (computer science),Artificial intelligence,Cascade,Pixel,Eye detection | Conference |
ISBN | Citations | PageRank |
978-1-4244-6963-5 | 0 | 0.34 |
References | Authors | |
17 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Samy Metari | 1 | 2 | 1.39 |
| F. Prel | 2 | 0 | 0.34 |
| T. Moszkowicz | 3 | 0 | 0.34 |
| D. Laurendeau | 4 | 31 | 8.67 |
| Normand Teasdale | 5 | 36 | 4.99 |
| S. Beauchemin | 6 | 0 | 0.34 |