Übersicht			Auf mobile öffnen

Lieferstatus:	Auf Bestellung (Lieferzeit unbekannt)
Veröffentlichung:	November 2012
Genre:	EDV / Informatik
	B / computer science / Computer Science, general / Computer Vision / Data Warehousing / Digitale Signalverarbeitung (DSP) / engineering / Graphical & digital media applications / Image processing / Image Processing and Computer Vision / Imaging systems & technology / Informatik / Information Retrieval / Information Storage and Retrieval / Multimedia Information Systems / Optical data processing / Signal Processing / Signal, Image and Speech Processing / Signal, Speech and Image Processing / Speech processing systems mehr...
ISBN:	9781461355861
EAN-Code:	9781461355861
Verlag:	Springer EN
Einband:	Kartoniert
Sprache:	English
Serie:	#639 - The Springer International Series in Engineering and Computer Science
Dimensionen:	H 235 mm / B 155 mm / D
Gewicht:	219 gr
Seiten:	109
Illustration:	XXI, 109 p.
Zus. Info:	EUDR exemption - product or manufacturing materials placed on the market prior to 31.12.2025.
Bewertung:	Titel bewerten / Meinung schreiben

Inhalt:

Semantic Video Object Segmentation for Content-Based MultimediaApplications provides a thorough review of state-of-the-art techniques as well as describing several novel ideas and algorithms for semantic object extraction from image sequences. Semantic object extraction is an essential element in content-based multimedia services, such as the newly developed MPEG4 and MPEG7 standards. An interactive system called SIVOG (Smart Interactive Video Object Generation) is presented, which converts user's semantic input into a form that can be conveniently integrated with low-level video processing. Thus, high-level semantic information and low-level video features are integrated seamlessly into a smart segmentation system. A region and temporal adaptive algorithm was further proposed to improve the efficiency of the SIVOG system so that it is feasible to achieve nearly real-time video object segmentation with robust and accurate performances. Also included is an examination of the shape coding problem and the object segmentation problem simultaneously. Semantic Video Object Segmentation for Content-Based MultimediaApplications will be of great interest to research scientists and graduate-level students working in the area of content-based multimedia representation and applications and its related fields.