A Low Complexity Euclidean Norm Approximation

Seol, Changkyu; Cheun, Kyungwhoon

doi:10.1109/tsp.2007.909354

Cited by 14 publications

(1 citation statement)

References 18 publications

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“…In order to minimise the computation time, an approximation of the computationally intensive L2 norm [37] is used for the descriptor normalisation. Furthermore, the division operation is not explicitly computed, but implicitly carried in the binarisation step described below.…”

Section: Spatio-angular Binarised Orientation Mapsmentioning

confidence: 99%

A Spatio-Angular Binary Descriptor For Fast Light Field Inter View Matching

Alain

Smolić

2020

2020 IEEE International Conference on Image Processing (ICIP)

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Light fields are able to capture light rays from a scene arriving at different angles, effectively creating multiple perspective views of the same scene. Thus, one of the flagship applications of light fields is to estimate the captured scene geometry, which can notably be achieved by establishing correspondences between the perspective views, usually in the form of a disparity map. Such correspondence estimation has been a long standing research topic in computer vision, with application to stereo vision or optical flow. Research in this area has shown the importance of well designed descriptors to enable fast and accurate matching. We propose in this paper a binary descriptor exploiting the light field gradient over both the spatial and the angular dimensions in order to improve inter view matching. We demonstrate in a disparity estimation application that it can achieve comparable accuracy compared to existing descriptors while being faster to compute.

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Section: Spatio-angular Binarised Orientation Mapsmentioning

confidence: 99%

A Spatio-Angular Binary Descriptor For Fast Light Field Inter View Matching

Alain

Smolić

2020

2020 IEEE International Conference on Image Processing (ICIP)

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An approximate logarithmic squaring circuit with error compensation for DSP applications

Avramović

Babić

Raič

et al. 2014

Microelectronics Journal

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On Euclidean norm approximations

Celebi

Celiker

Kingravi

2011

Pattern Recognition

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Euclidean norm calculations arise frequently in scientific and engineering applications. Several approximations for this norm with differing complexity and accuracy have been proposed in the literature. Earlier approaches [1,2,3] were based on minimizing the maximum error. Recently, Seol and Cheun [4] proposed an approximation based on minimizing the average error. In this paper, we first examine these approximations in detail, show that they fit into a single mathematical formulation, and compare their average and maximum errors. We then show that the maximum errors given by Seol and Cheun are significantly optimistic.

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A Low Complexity Euclidean Norm Approximation

Cited by 14 publications

References 18 publications

A Spatio-Angular Binary Descriptor For Fast Light Field Inter View Matching

A Spatio-Angular Binary Descriptor For Fast Light Field Inter View Matching

An approximate logarithmic squaring circuit with error compensation for DSP applications

On Euclidean norm approximations

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