• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利：CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法，用中文像聊天一样搜索，搜遍4000万医学文献。AI智能推荐，让科研检索更轻松。

立即免费搜索

文件翻译

保留排版，准确专业，支持PDF/Word/PPT等文件格式，支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述，25分钟生成高质量综述，智能提取关键信息，辅助科研写作。

立即免费体验

基于事件的高动态范围传感器颜色分割

Event-Based Color Segmentation With a High Dynamic Range Sensor.

作者信息

Marcireau Alexandre, Ieng Sio-Hoi, Simon-Chane Camille, Benosman Ryad B

机构信息

Institut National de la Santé et de la Recherche Médicale, UMRI S 968, Sorbonne Universites, UPMC Univ Paris 06, UMR S 968, Centre National de la Recherche Scientifique, UMR 7210, Institut de la Vision, Paris, France.

出版信息

Front Neurosci. 2018 Apr 11;12:135. doi: 10.3389/fnins.2018.00135. eCollection 2018.

DOI:10.3389/fnins.2018.00135
PMID:29695948
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5904265/
Abstract

This paper introduces a color asynchronous neuromorphic event-based camera and a methodology to process color output from the device to perform color segmentation and tracking at the native temporal resolution of the sensor (down to one microsecond). Our color vision sensor prototype is a combination of three Asynchronous Time-based Image Sensors, sensitive to absolute color information. We devise a color processing algorithm leveraging this information. It is designed to be computationally cheap, thus showing how low level processing benefits from asynchronous acquisition and high temporal resolution data. The resulting color segmentation and tracking performance is assessed both with an indoor controlled scene and two outdoor uncontrolled scenes. The tracking's mean error to the ground truth for the objects of the outdoor scenes ranges from two to twenty pixels.

摘要

本文介绍了一种彩色异步神经形态事件相机以及一种处理该设备彩色输出的方法，以便在传感器的原生时间分辨率（低至一微秒）下执行颜色分割和跟踪。我们的彩色视觉传感器原型是三个基于异步时间的图像传感器的组合，对绝对颜色信息敏感。我们设计了一种利用此信息的颜色处理算法。它被设计为计算成本低，从而展示了低级处理如何从异步采集和高时间分辨率数据中受益。通过一个室内受控场景和两个室外非受控场景对所得的颜色分割和跟踪性能进行了评估。室外场景中物体跟踪相对于地面真值的平均误差范围为两到二十像素。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/ade06ca9404b/fnins-12-00135-g0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/b8f6f6f9e3c4/fnins-12-00135-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/63728b14e76f/fnins-12-00135-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/456f7f7d20e5/fnins-12-00135-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/2c1ba5dd93bd/fnins-12-00135-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/ead13ea672ec/fnins-12-00135-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/74ae39afa43f/fnins-12-00135-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/7f76bbc49642/fnins-12-00135-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/d1e65d081146/fnins-12-00135-g0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/dc04dd2f302e/fnins-12-00135-g0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/ade06ca9404b/fnins-12-00135-g0010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/b8f6f6f9e3c4/fnins-12-00135-g0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/63728b14e76f/fnins-12-00135-g0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/456f7f7d20e5/fnins-12-00135-g0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/2c1ba5dd93bd/fnins-12-00135-g0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/ead13ea672ec/fnins-12-00135-g0005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/74ae39afa43f/fnins-12-00135-g0006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/7f76bbc49642/fnins-12-00135-g0007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/d1e65d081146/fnins-12-00135-g0008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/dc04dd2f302e/fnins-12-00135-g0009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1391/5904265/ade06ca9404b/fnins-12-00135-g0010.jpg

相似文献

1
Event-Based Color Segmentation With a High Dynamic Range Sensor.基于事件的高动态范围传感器颜色分割
Front Neurosci. 2018 Apr 11;12:135. doi: 10.3389/fnins.2018.00135. eCollection 2018.
2
A Saccade Based Framework for Real-Time Motion Segmentation Using Event Based Vision Sensors.一种基于扫视的框架，用于使用基于事件的视觉传感器进行实时运动分割。
Front Neurosci. 2017 Mar 3;11:83. doi: 10.3389/fnins.2017.00083. eCollection 2017.
3
Event-Based Tone Mapping for Asynchronous Time-Based Image Sensor.用于异步时间图像传感器的基于事件的色调映射
Front Neurosci. 2016 Aug 31;10:391. doi: 10.3389/fnins.2016.00391. eCollection 2016.
4
Neuromorphic Event-Based 3D Pose Estimation.基于神经形态事件的3D姿态估计
Front Neurosci. 2016 Jan 22;9:522. doi: 10.3389/fnins.2015.00522. eCollection 2015.
5
Bio-Inspired Asynchronous Pixel Event Tricolor Vision Sensor.生物启发式异步像素事件三色视觉传感器
IEEE Trans Biomed Circuits Syst. 2014 Jun;8(3):345-57. doi: 10.1109/TBCAS.2013.2271382. Epub 2013 Aug 6.
6
A Noise Filtering Algorithm for Event-Based Asynchronous Change Detection Image Sensors on TrueNorth and Its Implementation on TrueNorth.一种用于TrueNorth上基于事件的异步变化检测图像传感器的噪声滤波算法及其在TrueNorth上的实现
Front Neurosci. 2018 Mar 5;12:118. doi: 10.3389/fnins.2018.00118. eCollection 2018.
7
Neuromorphic Event-Based Generalized Time-Based Stereovision.基于神经形态事件的广义基于时间的立体视觉
Front Neurosci. 2018 Jul 2;12:442. doi: 10.3389/fnins.2018.00442. eCollection 2018.
8
Stabilization and Validation of 3D Object Position Using Multimodal Sensor Fusion and Semantic Segmentation.使用多模态传感器融合和语义分割技术稳定和验证三维物体位置。
Sensors (Basel). 2020 Feb 18;20(4):1110. doi: 10.3390/s20041110.
9
Improved Target Signal Source Tracking and Extraction Method Based on Outdoor Visible Light Communication Using a Cam-Shift Algorithm and Kalman Filter.基于 Cam-Shift 算法和卡尔曼滤波的户外可见光通信目标信号源跟踪与提取方法的改进。
Sensors (Basel). 2018 Nov 28;18(12):4173. doi: 10.3390/s18124173.
10
A Bio-Inspired AER Temporal Tri-Color Differentiator Pixel Array.一种生物启发的 AER 时间三分色区分器像素阵列。
IEEE Trans Biomed Circuits Syst. 2015 Oct;9(5):686-98. doi: 10.1109/TBCAS.2015.2492460. Epub 2015 Oct 30.

引用本文的文献

1
Velocity and Color Estimation Using Event-Based Clustering.基于事件聚类的速度与颜色估计
Sensors (Basel). 2023 Dec 11;23(24):9768. doi: 10.3390/s23249768.
2
Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review.基于事件的视觉、听觉和嗅觉域传感与信号处理：综述
Front Neural Circuits. 2021 May 31;15:610446. doi: 10.3389/fncir.2021.610446. eCollection 2021.

本文引用的文献

1
Color contributes to object-contour perception in natural scenes.颜色有助于在自然场景中感知物体轮廓。
J Vis. 2017 Mar 1;17(3):14. doi: 10.1167/17.3.14.
2
An Asynchronous Neuromorphic Event-Driven Visual Part-Based Shape Tracking.异步神经形态事件驱动的基于部分的视觉形状跟踪。
IEEE Trans Neural Netw Learn Syst. 2015 Dec;26(12):3045-59. doi: 10.1109/TNNLS.2015.2401834. Epub 2015 Mar 18.
3
Asynchronous Event-Based Multikernel Algorithm for High-Speed Visual Features Tracking.基于异步事件的多核算法在高速视觉特征跟踪中的应用。
IEEE Trans Neural Netw Learn Syst. 2015 Aug;26(8):1710-20. doi: 10.1109/TNNLS.2014.2352401. Epub 2014 Sep 16.
4
Asynchronous event-based binocular stereo matching.基于异步事件的双目立体匹配。
IEEE Trans Neural Netw Learn Syst. 2012 Feb;23(2):347-53. doi: 10.1109/TNNLS.2011.2180025.
5
Event-based visual flow.基于事件的视觉流。
IEEE Trans Neural Netw Learn Syst. 2014 Feb;25(2):407-17. doi: 10.1109/TNNLS.2013.2273537.
6
Event-based 3D reconstruction from neuromorphic retinas.基于事件的神经形态视网膜 3D 重建。
Neural Netw. 2013 Sep;45:27-38. doi: 10.1016/j.neunet.2013.03.006. Epub 2013 Mar 15.
7
Silicon retina with correlation-based, velocity-tuned pixels.具有基于相关性的速度调谐像素的硅视网膜。
IEEE Trans Neural Netw. 1993;4(3):529-41. doi: 10.1109/72.217194.
8
Boosting color saliency in image feature detection.增强图像特征检测中的颜色显著性
IEEE Trans Pattern Anal Mach Intell. 2006 Jan;28(1):150-6. doi: 10.1109/TPAMI.2006.3.
9
Ecological importance of trichromatic vision to primates.三色视觉对灵长类动物的生态重要性。
Nature. 2001 Mar 15;410(6826):363-6. doi: 10.1038/35066567.