Shawn Recker

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This paper presents a framework for N-view triangulation of scene points, which improves processing time and final reprojection error with respect to standard methods, such as linear triangulation. The framework introduces an angular error-based cost function, which is robust to outliers and inexpensive to compute, and designed such that simple adaptive(More)
This paper presents a novel, interactive visualization tool that allows for the analysis of scene structure uncertainty and its sensitivity to parameters in different multi-view scene reconstruction stages. Given a set of input cameras and feature tracks, the volume rendering-based approach first creates a scalar field from angular error measurements. The(More)
A comprehensive uncertainty, baseline, and noise analysis in computing 3D points using a recent L1-based triangulation algorithm is presented. This method is shown to be not only faster and more accurate than its main competitor, linear triangulation, but also more stable under noise and baseline changes. A Monte Carlo analysis of covariance and a(More)
This paper presents a novel framework for practical and accurate N-view triangulation of scene points. The algorithm is based on applying swarm optimization inside a robustly-computed bounding box, using an angular error-based L<sub>1</sub> cost function which is more robust to outliers and less susceptible to local minima than cost functions such as(More)
Despite nearly universal support for the IEEE 754 floating-point standard on modern general-purpose processors, a wide variety of more specialized processors do not provide hardware floating-point units and rely instead on integer-only pipelines. Ray tracing on these platforms thus requires an integer rendering process. Toward this end, we clarify the(More)
This paper presents a framework for GPU-accelerated N-view triangulation in multi-view reconstruction that improves processing time and final reprojection error with respect to methods in the literature. The framework uses an algorithm based on optimizing an angular error-based L<sub>1</sub> cost function and it is shown how adaptive gradient descent can be(More)
—Structure-from-Motion (SfM) applications attempt to reconstruct the three-dimensional (3D) geometry of an underlying scene from a collection of images, taken from various camera viewpoints. Traditional optimization techniques in SfM, which compute and refine camera poses and 3D structure, rely only on feature tracks, or sets of corresponding pixels,(More)
Given the recent advances in both photogrammetry and structure-from-motion, a pipeline that capitalizes on the strengths of both fields is now possible. This paper presents a hybrid system that uses photogrammetric information to improve the accuracy of structure-from-motion, which in turn provides a more dense reconstruction. The procedure maintains the(More)
—We present the general idea of using common tools from the field of scientific visualization to aid in the design, implementation and testing of computer vision algorithms, as a complementary and educational component to purely mathematics-based algorithms and results. The interaction between these two broad disciplines has been basically non-existent in(More)