Statistical angular error-based triangulation for efficient and accurate multi-view scene reconstruction | IEEE Conference Publication | IEEE Xplore

Statistical angular error-based triangulation for efficient and accurate multi-view scene reconstruction


Abstract:

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, su...Show More

Abstract:

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 gradient descent can be applied for convergence. Our method also presents a statistical sampling component based on confidence levels, that reduces the number of rays to be used for triangulation of a given feature track. It is shown how the statistical component yields a meaningful yet much reduced set of representative rays for triangulation, and how the application of the cost function on the reduced sample can efficiently yield faster and more accurate solutions. Results are demonstrated on real and synthetic data, where it is proven to significantly increase the speed of triangulation and optimize reprojection error in most cases. This makes it especially attractive for efficient triangulation of large scenes given the speed and low memory requirements.
Date of Conference: 15-17 January 2013
Date Added to IEEE Xplore: 07 March 2013
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Conference Location: Clearwater Beach, FL, USA

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