Titlebook: Image and Video Retrieval; Second International Erwin M. Bakker,Michael S. Lew,Xiang Sean Zhou Conference proceedings 2003 Springer-Verlag

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膠狀

Carbon-Monoxide

Chandelier

tattle

誓言

TRECVID: Benchmarking the Effectiveness of Information Retrieval Tasks on Digital Videoe on to implement these techniques they inevitably try to evaluate the performance of their techniques in practical situations. The difficulty with doing this is that there is no test collection or any environment in which the effectiveness of video IR or video IR sub-tasks, can be evaluated and com

卷發(fā)

Shape Feature Matching for Trademark Image Retrievalnt shape features (including those included in the recent MPEG-7 standard) and matching techniques in the retrieval of multi-component trademark images. Experiments were conducted within the framework of the ARTISAN shape retrieval system, and retrieval effectiveness assessed on a database of over 1

水獺

Central Object Extraction for Object-Based Image Retrieval object from a complex background. Interesting objects are generally located near the center of the image and contain regions with significant color distribution. The significant color is the more frequently co-occurred color near the center of the image than at the background of the image. A core o

BADGE

vitrectomy

A Closer Look at Boosted Image Retrievalques offer significant improvements over previous methods on classification tasks, little research has examined the application of techniques such as boosting to the problem of retrieval from image and video databases. This paper looks at boosting for image retrieval and classification, with a compa