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The problem of pose estimation arises in many areas of computer vision, including object recognition, object tracking, site inspection and updating, and autonomous navigation when scene models are available. We present a new algorithm, called SoftPOSIT, for determining the pose of a 3D object from a single 2D image when correspondences between model points(More)
We present a new robust line matching algorithm for solving the model-to-image registration problem. Given a model consisting of 3D lines and a cluttered perspective image of this model, the algorithm simultaneously estimates the pose of the model and the correspondences of model lines to image lines. The algorithm combines softassign for determining(More)
We present an object recognition algorithm that uses model and image line features to locate complex objects in high clutter environments. Finding correspondences between model and image features is the main challenge in most object recognition systems. In our approach, corresponding line features are determined by a three-stage process. The first stage(More)
Building facade detection is an important problem in computer vision, with applications in mobile robotics and semantic scene understanding. In particular, mobile platform localization and guidance in urban environments can be enabled with an accurate segmentation of the various building facades in a scene. Toward that end, we present a system for(More)
Localization and modeling of stairways by mobile robots can enable multi-floor exploration for those platforms capable of stair traversal. Existing approaches focus on either stairway detection or traversal, but do not address these problems in the context of path planning for the autonomous exploration of multi-floor buildings. We propose a system for(More)
Boosting has been widely used for discriminative modeling of objects in images. Conventionally, pixel- and patch-based features have been used, but recently, features defined on multilevel aggregate regions were incorporated into the boosting framework, and demonstrated significant improvement in object labeling tasks. In this paper, we further extend the(More)
Accurately determining the position and orientation of an observer (a vehicle or a human) in outdoor urban environments is an important and challenging problem. The standard approach is to use the Global Positioning System (GPS), but this system performs poorly near tall buildings where line of sight to a sufficient number of satellites cannot be obtained.(More)
The problem of pose estimation arises in many areas of computer vision, including object recognition, object tracking, site inspection and updating, and autonomous navigation when scene models are available. We present a new algorithm, called SoftPOSIT, for determining the pose of a 3D object from a single 2D image when correspondences between model points(More)
We extend the classical notion of computational visual saliency to multi-image data collected using a stationary pan-tilt-zoom (PTZ) camera by introducing the concept of consistency: the requirement that the set of generated saliency maps should each assign the same saliency value to unique regions of the environment that appear in more than one image. We(More)