Default image browsing interfaces on touch-based mobile devices provide limited support for image search tasks. To facilitate fast and convenient searches we propose an alternative interface that takes advantage of 3D graphics and arranges images on a rotatable globe according to color similarity. In a user study we compare the new design to the iPad's image browser. Results collected from 24 participants show that for color-sorted image collections the globe can reduce search time by 23% without causing more errors and that it is perceived as being fun to use and preferred over the standard browsing interface by 70% of the participants.
Digital video enables manifold ways of multimedia content interaction. Over the last decade, many proposals for improving and enhancing video content interaction were published. More recent work particularly leverages on highly capable devices such as smartphones and tablets that embrace novel interaction paradigms, for example, touch, gesture-based or physical content interaction. In this article, we survey literature at the intersection of Human-Computer Interaction and Multimedia. We integrate literature from video browsing and navigation, direct video manipulation, video content visualization, as well as interactive video summarization and interactive video retrieval. We classify the reviewed works by the underlying interaction method and discuss the achieved improvements so far. We also depict a set of open problems that the video interaction community should address in future.
We propose a novel video browsing approach that aims at optimally integrating traditional, machine-based retrieval methods with an interface design optimized for human browsing performance. Advanced video retrieval and filtering (e.g., via color and motion signatures, and visual concepts) on a desktop is combined with a storyboardbased interface design on a tablet optimized for quick, brute-force visual inspection. Both modules run independently but exchange information to significantly minimize the data for visual inspection and compensate mistakes made by the search algorithms.
Mobile devices like smartphones and tablets are becoming increasingly capable in terms of processing power. Although they are already used in computer vision, no comparable measurement experiments of the popular OpenCV framework have been made yet. We try to fill this gap by evaluating the performance of a set of typical OpenCV operations, on mobile devices like the iPad Air and iPhone 5S. We compare those results with the performance of a consumer grade laptop PC (MacBook Pro). Our tests span from simple image manipulation methods to keypoint detection and descriptor extraction as well as descriptor matching. Results show that the top performing device can match the performance of the PC up to 80 percent in specific operations.
As mobile devices become more and more pervasive, they are increasingly used to record and watch personal and professional videos. Common video browsers on smart phones and tablets, however, fail to provide users an efficient and engaging experience to browse through video content.In this demo paper, we present an early prototype for browsing videos on tablets: browsing video with a 3D filmstrip. A video is split up into equidistant, uniformly sampled time segments. The segments are represented by key-frames shown on the surface of a filmstrip, allowing an immediate overview of great parts of the video. Further, a user can scroll through the filmstrip, start playback for any segment and refine the preview of segments by simple touch gestures.
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