The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Pour l'acquisition d'informations visuelles, le processus d'échantillonnage non uniforme par les photorécepteurs de la rétine se produit dès le stade le plus précoce du traitement visuel. À partir des objets d'intérêt, l'œil humain reçoit une haute résolution visuelle grâce à une distribution non uniforme des photorécepteurs. Par conséquent, cet article propose des algorithmes d’exposition et de mise au point automatiques pour le système de caméra vidéo en temps réel, basés sur les caractéristiques visuelles de l’œil humain. Pour des objets en mouvement donnés, le poids visuel est modélisé pour quantifier l'importance visuelle et les paramètres d'exposition automatique et de mise au point associés sont dérivés en appliquant le poids à l'expression numérique traditionnelle, c'est-à-dire les méthodes DoM (différence de médiane) et Tenengrad pour la mise au point automatique. .
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Kwanghyun LEE, Suyoung PARK, Sanghoon LEE, "Object-Based Auto Exposure and Focus Algorithms Based on the Human Visual System" in IEICE TRANSACTIONS on Fundamentals,
vol. E92-A, no. 3, pp. 832-835, March 2009, doi: 10.1587/transfun.E92.A.832.
Abstract: For the acquisition of visual information, the nonuniform sampling process by photoreceptors on the retina occurs at the earliest stage of visual processing. From objects of interest, the human eye receives high visual resolution through nonuniform distribution of photoreceptors. Therefore, this paper proposes auto exposure and focus algorithms for the real-time video camera system based on the visual characteristic of the human eye. For given moving objects, the visual weight is modeled for quantifying the visual importance and the associated auto exposure and focus parameters are derived by applying the weight to the traditional numerical expression, i.e., the DoM (Difference of Median) and Tenengrad methods for auto focus.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.E92.A.832/_p
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@ARTICLE{e92-a_3_832,
author={Kwanghyun LEE, Suyoung PARK, Sanghoon LEE, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Object-Based Auto Exposure and Focus Algorithms Based on the Human Visual System},
year={2009},
volume={E92-A},
number={3},
pages={832-835},
abstract={For the acquisition of visual information, the nonuniform sampling process by photoreceptors on the retina occurs at the earliest stage of visual processing. From objects of interest, the human eye receives high visual resolution through nonuniform distribution of photoreceptors. Therefore, this paper proposes auto exposure and focus algorithms for the real-time video camera system based on the visual characteristic of the human eye. For given moving objects, the visual weight is modeled for quantifying the visual importance and the associated auto exposure and focus parameters are derived by applying the weight to the traditional numerical expression, i.e., the DoM (Difference of Median) and Tenengrad methods for auto focus.},
keywords={},
doi={10.1587/transfun.E92.A.832},
ISSN={1745-1337},
month={March},}
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TY - JOUR
TI - Object-Based Auto Exposure and Focus Algorithms Based on the Human Visual System
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 832
EP - 835
AU - Kwanghyun LEE
AU - Suyoung PARK
AU - Sanghoon LEE
PY - 2009
DO - 10.1587/transfun.E92.A.832
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E92-A
IS - 3
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - March 2009
AB - For the acquisition of visual information, the nonuniform sampling process by photoreceptors on the retina occurs at the earliest stage of visual processing. From objects of interest, the human eye receives high visual resolution through nonuniform distribution of photoreceptors. Therefore, this paper proposes auto exposure and focus algorithms for the real-time video camera system based on the visual characteristic of the human eye. For given moving objects, the visual weight is modeled for quantifying the visual importance and the associated auto exposure and focus parameters are derived by applying the weight to the traditional numerical expression, i.e., the DoM (Difference of Median) and Tenengrad methods for auto focus.
ER -