Recent Advances in Intelligent Image Search and Video Retrieval: Contributions to the 9th Workshop on Cyclostationary Systems and Their Applications, ... 2016 (Intelligent Systems Reference Library)
暫譯: 智能影像搜尋與影片檢索的最新進展:第九屆週期性系統及其應用研討會貢獻,... 2016(智能系統參考圖書館)
Bahman Zohuri, Masoud Moghaddam
- 出版商: Springer
- 出版日期: 2017-04-19
- 售價: $8,670
- 貴賓價: 9.5 折 $8,237
- 語言: 英文
- 頁數: 235
- 裝訂: Hardcover
- ISBN: 3319520806
- ISBN-13: 9783319520803
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商品描述
This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring.
Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant content from images and videos, a challenge this book addresses.This book initially reviews the major feature representation and extraction methods and effective learning and recognition approaches, which have broad applications in the context of intelligent image search and video retrieval. It subsequently presents novel methods, such as improved soft assignment coding, Inheritable Color Space (InCS) and the Generalized InCS framework, the sparse kernel manifold learner method, the efficient Support Vector Machine (eSVM), and the Scale-Invariant Feature Transform (SIFT) features in multiple color spaces. Lastly, the book presents clothing analysis for subject identification and retrieval, and performance evaluation methods of video analytics for traffic monitoring.
Digital images and videos are proliferating at an amazing speed in the fields of science, engineering and technology, media and entertainment. With the huge accumulation of such data, keyword searches and manual annotation schemes may no longer be able to meet the practical demand for retrieving relevant content from images and videos, a challenge this book addresses.
商品描述(中文翻譯)
本書最初回顧了主要的特徵表示與提取方法,以及有效的學習與識別方法,這些方法在智能圖像搜索和視頻檢索的背景下具有廣泛的應用。接著,本書介紹了新穎的方法,例如改進的軟分配編碼、可繼承顏色空間(Inheritable Color Space, InCS)和廣義InCS框架、稀疏核流形學習方法、高效支持向量機(efficient Support Vector Machine, eSVM)以及在多種顏色空間中的尺度不變特徵變換(Scale-Invariant Feature Transform, SIFT)特徵。最後,本書介紹了用於主體識別和檢索的服裝分析,以及用於交通監控的視頻分析性能評估方法。
數位圖像和視頻在科學、工程和技術、媒體和娛樂領域以驚人的速度增長。隨著這些數據的巨大累積,關鍵字搜索和手動標註方案可能無法滿足從圖像和視頻中檢索相關內容的實際需求,這是本書所要解決的挑戰。