ImageCLEF : Experimental Evaluation in Visual Information Retrieval

Unbekannt

ISBN 10: 3642264638 / ISBN 13: 9783642264634

Editore: Springer, 2012

Riguardo questo articolo

Zustand: Gut | Seiten: 572 | Sprache: Englisch | Produktart: Bücher | The pervasive creation and consumption of content, especially visual content, is ingrained into our modern world. We¿re constantly consuming visual media content, in printed form and in digital form, in work and in leisure pursuits. Like our cave¿ man forefathers, we use pictures to record things which are of importance to us as memory cues for the future, but nowadays we also use pictures and images to document processes; we use them in engineering, in art, in science, in medicine, in entertainment and we also use images in advertising. Moreover, when images are in digital format, either scanned from an analogue format or more often than not born digital, we can use the power of our computing and networking to exploit images to great effect. Most of the technical problems associated with creating, compressing, storing, transmitting, rendering and protecting image data are already solved. We use - cepted standards and have tremendous infrastructure and the only outstanding ch- lenges, apart from managing the scale issues associated with growth, are to do with locating images. That involves analysing them to determine their content, clas- fying them into related groupings, and searching for images. To overcome these challenges we currently rely on image metadata, the description of the images, - ther captured automatically at creation time or manually added afterwards.

Codice articolo 23063872/3

Dati bibliografici

• Titolo: ImageCLEF : Experimental Evaluation in Visual Information Retrieval
• Editore: Springer
• Data di pubblicazione: 2012
• Lingua: Inglese
• ISBN 10: 3642264638
• ISBN 13: 9783642264634
• Rilegatura: Brossura
• Condizione: Gut
• Cataloghi dei venditori:
  • Bücher

Descrizione articolo

Riassunto

The pervasive creation and consumption of content, especially visual content, is ingrained into our modern world. We re constantly consuming visual media content, in printed form and in digital form, in work and in leisure pursuits. Like our cave man forefathers, we use pictures to record things which are of importance to us as memory cues for the future, but nowadays we also use pictures and images to document processes; we use them in engineering, in art, in science, in medicine, in entertainment and we also use images in advertising. Moreover, when images are in digital format, either scanned from an analogue format or more often than not born digital, we can use the power of our computing and networking to exploit images to great effect. Most of the technical problems associated with creating, compressing, storing, transmitting, rendering and protecting image data are already solved. We use - cepted standards and have tremendous infrastructure and the only outstanding ch- lenges, apart from managing the scale issues associated with growth, are to do with locating images. That involves analysing them to determine their content, clas- fying them into related groupings, and searching for images. To overcome these challenges we currently rely on image metadata, the description of the images, - ther captured automatically at creation time or manually added afterwards.

Informazioni sull?autore

Henning Müller obtained his Masters degree in medical informatics from Heidelberg University, Germany in 1997 and his PhD on multimedia information retrieval from Geneva University, Switzerland in 2002. Since 2007 he has been a professor at the University of Applied Sciences Western Switzerland in Sierre. He has worked on visual information retrieval for over twelve years and on multimedia retrieval evaluation for almost the same amount of time. He has co-started the Benchathlon initiative on image retrieval evaluation and leads the ImageCLEF benchmark on multilingual and multimodal information retrieval. Henning Müller has published over 200 scientific articles and is currently in the editorial board of five journals. He has participated in several EU projects and has initiated several national projects.

 

Paul Clough is a lecturer in Information Systems in the Department of Information Studies, University of Sheffield (UK). He received his BEng from the University of York in Computer Science while also working for British Telecommunications Plc. as a software engineer. He received his PhD from the Department of Computer Science, University of Sheffield and has since worked as a researcher on a range of language engineering and information access projects. Clough is member of the Information Retrieval (IR) group, and his core research interests are information retrieval (geographical IR, multimedia IR and evaluation), computational text analysis (plagiarism detection, authorship attribution and creating corpora) and human-computer interaction. He has over 60 peer-reviewed publications in his research area and a US patent for an information management system.

 

Thomas Deselaers is a researcher at the Computer Vision Laboratory of ETH Zürich. He received his diploma and his PhD degree from RWTH Aachen University in Aachen, Germany in 2004 and 2008, respectively. From March 2004 to December 2008, he was a full-time researcher at the Human Language Technology and Pattern Recognition Group of the Computer Science Department of RWTH Aachen University, where he was the head of the image processing and understanding group from 2005-2008. In 2006 he was a research intern at Microsoft Research Cambridge, UK. His research interests are object classification and detection in complex scenes, content-based image retrieval, and pattern recognition.

 

Barbara Caputo is a senior research scientist (permanent position) at the Idiap Research Institute, Switzerland, since 2006 where she leads the Cognitive Visual Systems group. She received her PhD in Computer Science from the Royal Institute of Technology (KTH) in Stockholm, Sweden, in 2004. Her main research interest is in Vision for Robotics. This is a new emerging domain that aims at providing robots with visual capabilities similar to those of humans. This domain intersects the well-established research fields of computer vision, machine learning and robotics, where she has been active since 1999. As a result of her activities, she has edited two books, and she has published more than 40 papers in international journals and peer reviewed conferences. As of today, Barbara Caputo has been Principal Investigator and co-Principal Investigator of seven European and National projects.