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Content-based video copy detection is very important for copyright protection in view of the growing popularity of video sharing websites, which deals with not only whether a copy occurs in a query video stream but also where the copy is located and where the copy is originated from. While a lot of work has addressed the problem with good performance, less effort has been made to consider the copy...
This paper proposes a new method to automatically index searches for relevant images using geo-coded information. Photographic images are labeled with their GPS (Global Positioning System) coordinates and date/time at the moment of capture and this date is then utilized to create two layer spatial and temporal indexes for image searches. A simulation performed to estimate the effectiveness of the...
We study the task of detecting the occurrence of objects in large image collections or in videos, a problem that combines aspects of content based image retrieval and object localization. While most previous approaches are either limited to special kinds of queries, or do not scale to large image sets, we propose a new method, efficient subimage retrieval (ESR), that is at the same time very flexible...
In the demonstration we will show a system for searching by similarity and automatically classifying images in a very large dataset. The demonstrated techniques are based on the use of the MI-File (Metric Inverted File) as the access method for executing similarity search efficiently. The MI-File is an access methods based on inverted files that relies on a space transformation that use the notion...
We propose a probabilistic model for the relevance feedback of users looking for target images. This model takes into account user errors and user uncertainty about distinguishing similarly relevant images. Based on this model, we have developed an algorithm, which selects images to be presented to the user for further relevance feedback until a satisfactory image is found. In each query session,...
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