Summed-area tables for texture mapping

Crow, Franklin C.

doi:10.1145/964965.808600

Cited by 651 publications

(227 citation statements)

References 7 publications

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“…It was first introduced to the computer graphics field in [53] to be used in mipmaps. Viola-Jones face detector applied the integral image for rapid computation of Haar-like features, as detailed below.…”

Section: The Integral Imagementioning

confidence: 99%

A survey on face detection in the wild: Past, present and future

Zafeiriou

Cha

Zhang

2015

Computer Vision and Image Understanding

381

167

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Section: The Integral Imagementioning

confidence: 99%

A survey on face detection in the wild: Past, present and future

Zafeiriou

Cha

Zhang

2015

Computer Vision and Image Understanding

381

167

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“…Since blocks for the p-th patch have the same number of pixels, sums of their intensities (I (B j p )) can be compared. This solution is motivated by efficient calculation of such sums using the integral image technique [3,27]. Also, the firstorder intensity gradients in the x and y directions (D x (B j p ) and D y (B j p )) are computed using Haar-like box filters and the integral image, as in SURF [3].…”

Section: Optimisation Problemmentioning

confidence: 99%

An optimisation approach to the design of a fast, compact and distinctive binary descriptor

Oszust

2016

SIViP

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The desired local feature descriptor should be distinctive, compact and fast to compute and match. Therefore, many computer vision applications use binary keypoint descriptors instead of floating-point, rich techniques. In this paper, an optimisation approach to the design of a binary descriptor is proposed, in which the detected keypoint is described using several, scale-dependent patches. Each such patch is divided into disjoint blocks of pixels, and then, binary tests between blocks' intensities, as well as their gradients, are used to obtain the binary string. Since the number of image patches and their relative sizes influence the descriptor creation pipeline, a simulated annealing algorithm is used to determine them, optimising recall and precision of keypoint matching. The simulated annealing is also used for dimensionality reduction in long binary strings. The proposed approach is extensively evaluated and compared with SIFT, SURF and BRIEF on public benchmarks. Obtained results show that the binary descriptor created using the resulted pipeline is faster to compute and yields comparable or better performance than the state-of-the-art descriptors under different image transformations.

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“…Summed Area Tables (SAT) were first introduced in 1984 by Crow [22]. It is possible to think of an SAT as an integral of a texture.…”

Section: Summed Area Tablesmentioning

confidence: 99%

Adaptively layered statistical volumetric obscurance

Hendrickx

Scandolo

Eisemann

et al. 2015

Proceedings of the 7th Conference on High-Performance Graphics

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We accelerate volumetric obscurance, a variant of ambient occlusion, and solve undersampling artifacts, such as banding, noise or blurring, that screen-space techniques traditionally suffer from. We make use of an efficient statistical model to evaluate the occlusion factor in screen-space using a single sample. Overestimations and halos are reduced by an adaptive layering of the visible geometry. Bias at tilted surfaces is avoided by projecting and evaluating the volumetric obscurance in tangent space of each surface point. We compare our approach to several traditional screen-space volumetric obscurance techniques and show its competitive qualitative and quantitative performance. Our algorithm maps well to graphics hardware, does not require the traditional bilateral blur step of previous approaches, and avoids typical screen-space related artifacts such as temporal instability due to undersampling.iii PREFACE

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Summed-area tables for texture mapping

Cited by 651 publications

References 7 publications

A survey on face detection in the wild: Past, present and future

A survey on face detection in the wild: Past, present and future

An optimisation approach to the design of a fast, compact and distinctive binary descriptor

Adaptively layered statistical volumetric obscurance

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