基于深度学习的视频场景目标定位方法

A. Lee, S. Yong
{"title":"基于深度学习的视频场景目标定位方法","authors":"A. Lee, S. Yong","doi":"10.1109/SPC.2018.8704126","DOIUrl":null,"url":null,"abstract":"The ultimate goal of computer vision research is to understand a scene semantically from an image or a video. Real-time object detection received significant attention over the past few years. Many challenges remain, especially in the focus of extraction of localized object information for scene representation. In order to have an accurate, intelligent and fast real-time object detection, the implementation of accurate localized information in the machine is inevitable. This research will focus on developing the object localization extractor that can extract the localized object information from the scene for further scene prediction and inference. In particular, (i) our localized extractor can encode significantly high-level features information; (ii) this rich localized information will be used for scene representation and understanding.","PeriodicalId":432464,"journal":{"name":"2018 IEEE Conference on Systems, Process and Control (ICSPC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Localized Object Information from Detected Objects Based on Deep Learning in Video Scene\",\"authors\":\"A. Lee, S. Yong\",\"doi\":\"10.1109/SPC.2018.8704126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The ultimate goal of computer vision research is to understand a scene semantically from an image or a video. Real-time object detection received significant attention over the past few years. Many challenges remain, especially in the focus of extraction of localized object information for scene representation. In order to have an accurate, intelligent and fast real-time object detection, the implementation of accurate localized information in the machine is inevitable. This research will focus on developing the object localization extractor that can extract the localized object information from the scene for further scene prediction and inference. In particular, (i) our localized extractor can encode significantly high-level features information; (ii) this rich localized information will be used for scene representation and understanding.\",\"PeriodicalId\":432464,\"journal\":{\"name\":\"2018 IEEE Conference on Systems, Process and Control (ICSPC)\",\"volume\":\"28 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE Conference on Systems, Process and Control (ICSPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPC.2018.8704126\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE Conference on Systems, Process and Control (ICSPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPC.2018.8704126","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

计算机视觉研究的最终目标是从图像或视频中理解场景的语义。实时目标检测在过去几年中受到了极大的关注。目前仍存在许多挑战,特别是在场景表示中局部对象信息的提取方面。为了实现准确、智能、快速的实时目标检测,在机器中实现准确的定位信息是必然的。本研究将重点开发目标定位提取器,从场景中提取出定位后的目标信息,用于进一步的场景预测和推理。特别是,(i)我们的局部提取器可以编码显著的高级特征信息;(ii)这些丰富的本地化信息将用于场景表示和理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Localized Object Information from Detected Objects Based on Deep Learning in Video Scene
The ultimate goal of computer vision research is to understand a scene semantically from an image or a video. Real-time object detection received significant attention over the past few years. Many challenges remain, especially in the focus of extraction of localized object information for scene representation. In order to have an accurate, intelligent and fast real-time object detection, the implementation of accurate localized information in the machine is inevitable. This research will focus on developing the object localization extractor that can extract the localized object information from the scene for further scene prediction and inference. In particular, (i) our localized extractor can encode significantly high-level features information; (ii) this rich localized information will be used for scene representation and understanding.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
The Effect of Foot Arch on Plantar Distribution During Running A Comparative Study of Valve Stiction Compensation: Knocker Based Methods Design and Implement SumoBot for Classroom Teaching Vibration Control of a Nonlinear Double-Pendulum Overhead Crane Using Feedforward Command Shaping Mother Wavelet Selection for Control Valve Leakage Detection using Acoustic Emission
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1