.png){kind=icon}
返回
A component-based framework for face detection and identification
.png){kind=icon}
PRE
AI
DOI：10.1007/s11263-006-0006-z.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
We present a component-based framework for face detection and identification. The face detection and identification modules share the same hierarchical architecture. They both consist of two layers of classifiers, a layer with a set of component classifiers and a layer with a single combination classifier. The component classifiers independently detect/identify facial parts in the image. Their outputs are passed the combination classifier which performs the final detection/identification of the face. We describe an algorithm which automatically learns two separate sets of facial components for the detection and identification tasks. In experiments we compare the detection and identification systems to standard global approaches. The experimental results clearly show that our component-based approach is superior to global approaches.
Keyword:
face detection
face identification
face recognition
object detection
object recognition
support vector machines
components
fragments
parts
hierarchical classification
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.3
论文数:
3.9K
被引数:
2.8W
机构
暂无机构信息
引用论文
分享收藏Cross-Cultural Application of the Korean Version of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire for Patients with Prostate Cancer - EORTC QLQ-PR25.png)
Oncology
OncologyIF0
PREAI
分享收藏
分享收藏
查看更多内容