Computer Vision in the Infrared Spectrum: Challenges and Approaches
暫譯: 紅外光譜中的計算機視覺：挑戰與方法
Michael Teutsch , Angel D. Sappa , Riad I. Hammoud
- 出版商: Morgan & Claypool
- 出版日期: 2021-10-27
- 售價: $1,930
- 貴賓價: 9.5 折 $1,834
- 語言: 英文
- 頁數: 138
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1636392415
- ISBN-13: 9781636392417
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相關分類:
Computer Vision
海外代購書籍(需單獨結帳)
商品描述
Human visual perception is limited to the visual-optical spectrum. Machine vision is not. Cameras sensitive to the different infrared spectra can enhance the abilities of autonomous systems and visually perceive the environment in a holistic way. Relevant scene content can be made visible especially in situations, where sensors of other modalities face issues like a visual-optical camera that needs a source of illumination. As a consequence, not only human mistakes can be avoided by increasing the level of automation, but also machine-induced errors can be reduced that, for example, could make a self-driving car crash into a pedestrian under difficult illumination conditions. Furthermore, multi-spectral sensor systems with infrared imagery as one modality are a rich source of information and can provably increase the robustness of many autonomous systems. Applications that can benefit from utilizing infrared imagery range from robotics to automotive and from biometrics to surveillance. In this book, we provide a brief yet concise introduction to the current state-of-the-art of computer vision and machine learning in the infrared spectrum. Based on various popular computer vision tasks such as image enhancement, object detection, or object tracking, we first motivate each task starting from established literature in the visual-optical spectrum. Then, we discuss the differences between processing images and videos in the visual-optical spectrum and the various infrared spectra. An overview of the current literature is provided together with an outlook for each task. Furthermore, available and annotated public datasets and common evaluation methods and metrics are presented. In a separate chapter, popular applications that can greatly benefit from the use of infrared imagery as a data source are presented and discussed. Among them are automatic target recognition, video surveillance, or biometrics including face recognition. Finally, we conclude with recommendations for well-fitting sensor setups and data processing algorithms for certain computer vision tasks. We address this book to prospective researchers and engineers new to the field but also to anyone who wants to get introduced to the challenges and the approaches of computer vision using infrared images or videos. Readers will be able to start their work directly after reading the book supported by a highly comprehensive backlog of recent and relevant literature as well as related infrared datasets including existing evaluation frameworks. Together with consistently decreasing costs for infrared cameras, new fields of application appear and make computer vision in the infrared spectrum a great opportunity to face nowadays scientific and engineering challenges.
商品描述(中文翻譯)
人類的視覺感知僅限於可見光光譜，而機器視覺則不然。對不同紅外光譜敏感的相機可以增強自主系統的能力，並以整體的方式視覺感知環境。在某些情況下，相關場景內容可以變得可見，特別是當其他模態的感測器面臨問題時，例如需要光源的可視光相機。因此，透過提高自動化水平，不僅可以避免人為錯誤，還可以減少機器引起的錯誤，例如在困難的照明條件下使自駕車撞上行人。此外，具有紅外影像作為一種模態的多光譜感測器系統是豐富的信息來源，並且可以顯著提高許多自主系統的穩健性。可以從機器人技術到汽車，從生物識別到監控等應用中受益於利用紅外影像。本書提供了對紅外光譜中計算機視覺和機器學習的最新技術狀態的簡要而精煉的介紹。基於各種流行的計算機視覺任務，如影像增強、物體檢測或物體追蹤，我們首先從可見光光譜的既有文獻出發，激勵每個任務。然後，我們討論在可見光光譜和各種紅外光譜中處理影像和視頻的差異。提供了當前文獻的概述，並對每個任務進行展望。此外，還介紹了可用的標註公共數據集以及常見的評估方法和指標。在單獨的一章中，介紹並討論了可以從使用紅外影像作為數據來源中獲益良多的流行應用，包括自動目標識別、視頻監控或生物識別（包括面部識別）。最後，我們總結了對於某些計算機視覺任務的合適感測器設置和數據處理算法的建議。我們將本書針對對該領域感興趣的潛在研究人員和工程師，同時也適合任何希望了解使用紅外影像或視頻的計算機視覺挑戰和方法的人士。讀者在閱讀本書後將能夠直接開始他們的工作，並得到最新和相關文獻的全面支持，以及相關的紅外數據集，包括現有的評估框架。隨著紅外相機成本的持續下降，新的應用領域出現，使得紅外光譜中的計算機視覺成為應對當今科學和工程挑戰的絕佳機會。
作者簡介
Michael Teutsch received his diploma degree in computer science and his PhD degree from the Karlsruhe Institute of Technology (KIT) in 2009 and 2014, respectively. From 2009 to 2016, he worked as a research scientist and a postdoc at the Fraun- hofer IOSB, Karlsruhe, Germany. Since 2016, he has been with Hensoldt Optron- ics, Oberkochen, Germany. His research interests include computer vision, visual surveillance, object detection, object tracking, and machine learning. Michael has been organizing and co-chairing the annual IEEE International Workshop on Percep- tion Beyond the Visible Spectrum (PBVS) in conjunction with the IEEE International Conference on Computer Vision and Pattern Recognition (CVPR) since 2018. He is active as lecturer in computer vision currently at the Baden-Wuerttemberg Coop- erative State University (DHBW) Heidenheim, Germany. Michael serves as reviewer for several journals and conferences such as IEEE Transactions on Pattern Analysis and Machine Intelligences (TPAMI), IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), or IEEE Transactions on Geoscience and Remote Sens- ing (TGRS). He has authored or co-authored more than 30 scientific publications.
Angel D. Sappa received his Electro Mechanical Engineering degree (1995) from National University of La Pampa, Argentina, and his PhD degree in Industrial Engi- neering (1999) from Polytechnic University of Catalonia, Barcelona, Spain. In 2003, after research positions in France (LAAS-CNRS), the UK (UK Advanced Robotics) and Greece (ITI-CERTH), he joined the Computer Vision Center, Barcelona, Spain, where he currently holds a Senior Scientist position. Since 2016 he is a full professor at the ESPOL Polytechnic University, Guayaquil, Ecuador, where he leads the com- puter vision team at CIDIS research center; he is the director of the Electrical Engi- neering PhD program. His research interests include cross-spectral image processing and representation; 3D data acquisition, processing, and modeling; and computer vi- sion applications. He published about 200 papers in international journals and con- ference proceedings and served as program committee member in several interna- tional conferences. He has been involved in several national, regional and interna- tional research projects and several technological transfer projects; he has been the cofounder of VINTRA Inc. (San Francisco, USA) and Crowdmobile S.L. (Barcelona, Spain). He is a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).
Riad I. Hammoud received a MS degree in Controls of Systems and a PhD in Com- puter Vision and Robotics from UTC and INRIA (France) late 1997 and early 2001, respectively. He did his postdoc at Indiana University in 2002. Since early 2003, he is been working on several projects involving infrared imaging for defense, au- tomotive, and robotics applications. Early 2019, he joined TuSimple to develop au- tonomous driving systems. From 2012 to 2019, he worked at BAE Systems (Boston, MA, USA), on DARPA, AFRL and other US government agencies advanced research projects as principal investigator (PI), team lead and research scientist. Before joining BAE Systems, Riad was at Tobii-Dynavox (Pittsburgh, PA, USA) and Delphi Automo- tive Systems (Kokomo, IN, USA) working on Assistive Technologies and Active Safety Systems. He joined Seth Teller's team at MIT as a collaborating Researcher to work on the DARPA Robotics Challenge (2012-2015). Dr. Riad Hammoud served as guest editor of several special issues of top journals in computer vision including CVIU and IJCV. He authored several edited book including the Springer book on Augmented Vision Perception in Infrared. Since 2004, he has been organizing and chairing a workshop series in conjunction with the IEEE CVPR on Perception Beyond the Visible Spectrum (PBVS). He also serves as the general chair of SPIE Automatic Target Recognition conference (2018-2021).
作者簡介(中文翻譯)
**Michael Teutsch**於2009年和2014年分別獲得卡爾斯魯厄理工學院（Karlsruhe Institute of Technology, KIT）計算機科學學士學位和博士學位。從2009年到2016年，他在德國卡爾斯魯厄的弗勞恩霍夫IOSB擔任研究科學家和博士後研究員。自2016年以來，他一直在德國奧伯科亨的Hensoldt Optronics工作。他的研究興趣包括計算機視覺、視覺監控、物體檢測、物體追蹤和機器學習。自2018年以來，Michael一直在IEEE國際計算機視覺與模式識別會議（CVPR）上組織並共同主持年度IEEE國際可見光譜之外的感知研討會（PBVS）。他目前在德國海登海姆的巴登-符騰堡應用科技大學（DHBW）擔任計算機視覺講師。Michael擔任多個期刊和會議的審稿人，如IEEE模式分析與機器智能學報（TPAMI）、IEEE視頻技術電路與系統學報（TCSVT）和IEEE地球科學與遙感學報（TGRS）。他已發表或共同發表超過30篇科學出版物。
**Angel D. Sappa**於1995年獲得阿根廷拉潘帕國立大學的電機機械工程學位，並於1999年獲得西班牙巴塞隆納加泰羅尼亞理工大學的工業工程博士學位。2003年，在法國（LAAS-CNRS）、英國（UK Advanced Robotics）和希臘（ITI-CERTH）擔任研究職位後，他加入了西班牙巴塞隆納的計算機視覺中心，目前擔任高級科學家。自2016年以來，他在厄瓜多爾瓜亞基爾的ESPOL理工大學擔任全職教授，並領導CIDIS研究中心的計算機視覺團隊；他是電氣工程博士課程的主任。他的研究興趣包括跨光譜影像處理與表示、3D數據獲取、處理與建模，以及計算機視覺應用。他在國際期刊和會議論文集中發表了約200篇論文，並在多個國際會議中擔任程序委員會成員。他參與了多個國家、區域和國際研究項目以及多個技術轉移項目；他是VINTRA Inc.（美國舊金山）和Crowdmobile S.L.（西班牙巴塞隆納）的共同創辦人。他是電氣與電子工程師學會（IEEE）的高級會員。
**Riad I. Hammoud**於1997年底和2001年初分別獲得UTC和法國INRIA的系統控制碩士學位和計算機視覺與機器人學博士學位。他於2002年在印第安納大學完成博士後研究。自2003年初以來，他一直參與多個涉及紅外成像的防禦、汽車和機器人應用的項目。2019年初，他加入TuSimple開發自動駕駛系統。從2012年到2019年，他在BAE Systems（美國麻薩諸塞州波士頓）擔任主要研究員（PI）、團隊負責人和研究科學家，參與DARPA、AFRL和其他美國政府機構的先進研究項目。在加入BAE Systems之前，Riad曾在Tobii-Dynavox（美國賓夕法尼亞州匹茲堡）和Delphi Automotive Systems（美國印第安納州科科莫）從事輔助技術和主動安全系統的工作。他加入麻省理工學院的Seth Teller團隊，作為合作研究員參與DARPA機器人挑戰賽（2012-2015）。Riad Hammoud博士曾擔任多個計算機視覺頂級期刊的特刊客座編輯，包括CVIU和IJCV。他編輯了多本書籍，包括Springer出版的《紅外增強視覺感知》。自2004年以來，他一直在IEEE CVPR會議上組織並主持可見光譜之外的感知研討會（PBVS）。他還擔任SPIE自動目標識別會議的總主席（2018-2021）。
