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In recent years, see-through display technology has begun to reach a point where we will have the ability to continuously display virtual information in a variety of real world situations. However, augmented reality (AR) interfaces are currently limited in their ability to interact with the wearer and environment to provide specific, safe, and useful information when needed. Moreover, many questions...
For autonomous robots to operate successfully in unknown environments, their computer vision algorithms need to generalize over many different environments. However, due to practical considerations robotic vision experiments are typically limited to a single robot and a few (laboratory) environments. We propose crowdsourcing as a methodology for gathering large and varied robotic data sets. We evaluate...
Mobile visual search systems compare images against a database for object recognition. If query data is transmitted over a slow network or processed on a congested server, the latency increases substantially. This article shows how on-device database matching guarantees fast recognition regardless of external conditions. The database signatures must be compact because of limited memory, capable of...
We present a new system that assists people's reading activity by combining a wearable eye tracker, a see-through head mounted display, and an image based document retrieval engine. An image based document retrieval engine is used for identification of the reading document, whereas an eye tracker is used to detect which part of the document the reader is currently reading. The reader can refer to...
Recent mobile device and vision technology advances have enabled mobile Augmented Reality (AR) to be serviced in real-time using natural features. However, in viewing augmented reality while moving about, the user is always encountering new and diverse target objects in different locations. Whether the AR system is scalable or not to the number of target objects is an important issue for future mobile...
We present a retrieval-based tracking system that requires less computational time and cost. The system tracks a user's location through a small portion of an image captured by the camera, and then refines the camera pose by propagating matchings to the whole image. Augmented information such as building names and locations will be delivered to the user. The progressive way to process image data not...
In this paper we present a system for mobile augmented reality (AR) based on visual recognition. We split the tasks of recognizing an object and tracking it on the user's screen into a server-side and a client-side task, respectively. The capabilities of this hybrid client-server approach are demonstrated with a prototype application on the Android platform, which is able to augment both stationary...
Tracking is a major issue of virtual and augmented reality applications. Single object tracking on monocular video streams is fairly well understood. However, when it comes to multiple objects, existing methods lack scalability and can recognize only a limited number of objects. Thanks to recent progress in feature matching, state-of-the-art image retrieval techniques can deal with millions of images...
In this paper we present a new vision-based approach for transmitting virtual models for augmented reality (AR). A two dimensional representation of the virtual models is embedded in a printed image. We apply image-processing techniques to interpret the printed image and extract the virtual models, which are then overlaid back on the printed image. The main advantages of our approach are: (1) the...
The main objective of the CONNECT project is to create a pedagogical framework that attempts to blend informal and formal learning and to situate learning in real-world contexts. The introduction of a technologically advanced approach for learning by connecting a wide range of learning environments (school, home, science museums, research centers, science thematic parks and exhibitions) and the bridging...
We review some recent techniques for 3D tracking and occlusion handling for computer vision-based augmented reality. We discuss what their limits for real applications are, and why object recognition techniques are certainly the key to further improvements.
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