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Natural scene features stabilize and extend the tracking range of augmented reality (AR) pose-tracking systems. We develop robust computer vision methods to detect and track natural features in video images. Point and region features are automatically and adaptively selected for properties that lead to robust tracking. A multistage tracking algorithm(More)
In this paper, we address the complex problem of rapid modeling of large-scale areas and present a novel approach for the automatic reconstruction of cities from remote sensor data. The goal in this work is to automatically create lightweight, watertight polygonal 3D models from LiDAR data (Light Detection and Ranging) captured by an airborne scanner. This(More)
The biggest single obstacle to building effective augmented reality (AR) systems is the lack of accurate wide-area sensors for trackers that report the locations and orientations of objects in an environment. Active (sensor-emitter) tracking technologies require powereddevice installation, limiting their use to prepared areas that are relatively free of(More)
We present a wide-baseline image matching approach based on line segments. Line segments are clustered into local groups according to spatial proximity. Each group is treated as a feature called a Line Signature. Similar to local features, line signatures are robust to occlusion, image clutter, and viewpoint changes. The descriptor and similarity measure of(More)
The biggest single obstacle to building effective augmented reality (AR) systems is the lack of accurate wide-area sensors for tracking the locations and orientations of objects in an environment. Active (sensor-emitter) tracking technologies require powered-device installation, limiting their use to prepared areas that are relatively free of natural or(More)
We present an efficient and accurate object tracking algorithm based on the concept of graph cut segmentation. The ability to track visible objects in real-time provides an invaluable tool for the implementation of markerless Augmented Reality. Once an object has been detected, it’s location in future frames can be used to position virtual content, and thus(More)
models for development planning as well as climate, air quality, fire propagation, and public safety studies. Commercial users include phone, gas, and electric companies. Most of these users are primarily interested in models of buildings, terrain, vegetation, and traffic networks. A European Organization for Experimental Photogrammetric Research survey on(More)
Recent advances in sensing and computing technologies have inspired a new generation of data analysis and visualization systems for video surveillance applications. We present a novel visualization system for video surveillance based on an Augmented Virtual Environment (AVE) that fuses dynamic imagery with 3D models in a real-time display to help observers(More)