Christoph Korinke

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We present the concept of an interactive image segmentation method, which allows a fast and precise extraction of foreground objects from natural images. The method is especially suited for mobile, touch-based devices. The approach combines automatic image segmentation with interactive refinement. In a first step, the user extracts an object using the first(More)
Photo taking is more and more moving to mobile devices. With this transition, we observe that consumers are also directly editing and sharing photos. Editing of the whole image became very popular, for example with the filters Instagram offers. Some effects, however, require to edit a specific object of an image and for this an interactive segmentation is(More)
Images and videos are easy to create by inexperienced users with intuitive devices like smartphones. We propose a system which enables users to extract panoramas from videos for the creation of collages which can be printed. Single frames used for panoramas are indexed on the basis of SURF features. As a result users can make a photo with the smartphone(More)
Existing interactive image segmentation approaches mainly focus on the algorithms rather than the input methods. The literature regarding the input methods is mainly applied to desktop PCs. However, there is a transition to mobile touch-based devices. In this paper we describe our approach to identify a set of intuitive input methods for interactive(More)
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