Cortical 3D Face and Object Recognition Using 2D Projections

Author:

Rodrigues João1,Lam Roberto1,du Buf Hans1

Affiliation:

1. University of the Algarve, Portugal

Abstract

Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. In cortical area V1 exist double-opponent colour blobs, also simple, complex and end-stopped cells which provide input for a multiscale line/edge representation, keypoints for dynamic feature routing, and saliency maps for Focus-of-Attention. All these combined allow faces to be segregated. Events of different facial views are stored in memory and combined to identify the view and recognise a face, including its expression. In this paper, the authors show that with five 2D views and their cortical representations it is possible to determine the left-right and frontal-lateral-profile views, achieving a view-invariant recognition rate of 91%. The authors also show that the same principle with eight views can be applied to 3D object recognition when they are mainly rotated about the vertical axis.

Publisher

IGI Global

Subject

General Medicine

Reference43 articles.

1. 2D and 3D face recognition: A survey

2. Agbinya, J. I., & Silva, S. D. (2005). Face recognition programming on mobile handsets. In Proceedings of the 12th International Conference on Telecommunications, Cape Town, South Africa (pp. 3-6).

3. Visual objects in context

4. 3D Face Recognition Using Isogeodesic Stripes

5. Strange vision: ganglion cells as circadian photoreceptors

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. 3D object recognition and classification: a systematic literature review;Pattern Analysis and Applications;2019-02-27

2. Face and Object Recognition Using Biological Features and Few Views;Advances in Systems Analysis, Software Engineering, and High Performance Computing;2014

3. A proposed PCNN features quality optimization technique for pose-invariant 3D Arabic sign language recognition;Applied Soft Computing;2013-04

4. Fast Facial Detection by Depth Map Analysis;Mathematical Problems in Engineering;2013

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3