Catadioptric vision system for an optimal observation of the driver face and the road scene

Layerle, Jean-Francois; Savatier, Xavier; Mouaddib, El Mustapha; Ertaud, Jean-Yves

doi:10.1109/ivs.2008.4621269

Cited by 3 publications

(9 citation statements)

References 11 publications

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“…A large variety of formats are used in digital cameras, from less than 4 mm width on smart-phones (Maître 2017) to 200 mm on highly sensitive cameras for sky observation (Sako et al 2016). The diagonal of image sensors is chosen to fit into the circle of definition in order to minimize image blurriness (Langford 2000). The photodiodes, also called photosites, or photodetectors, but mostly known as pixels, convert the incoming light photons on the image plane into pixel brightness, coded on several bits (Maître 2017).…”

Section: The Image Sensormentioning

confidence: 99%

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A Survey on Adaptive Cameras

Ducrocq,

Caron

2024

Int J Comput Vis

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HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L'archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d'enseignement et de recherche français ou étrangers, des laboratoires publics ou privés.

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Section: The Image Sensormentioning

confidence: 99%

“…The circle of illumination (Sec. 2.2), which is bigger than the sensor, is thus moved relatively to the image sensor (Langford 2000). The image is then virtually translated, or rotated, by approximately the same distance as the lens actually is (Stroebel 1999).…”

Section: Moving Lensesmentioning

confidence: 99%

A Survey on Adaptive Cameras

Ducrocq,

Caron

2024

Int J Comput Vis

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“…Several methods exist to design a static mirror shape to capture scene regions with a desired resolution, e.g. with vector fields [20] or polynomial functions [21].…”

Section: Mirror Shape Optimizationmentioning

confidence: 99%

“…On the one hand, optimized mirrors are made once, e.g. to be put in cars for the driver gaze check while observing the surrounding road [20], or to be put at the center of crossroads for traffic monitoring [21]. On the other hand, existing DM-based adaptive cameras are aimed to capture astrophotographs [18] or retinal images [23], requiring a µm-scale stroke at high frequency.…”

Section: Mirror Shape Optimizationmentioning

confidence: 99%

Visadapt: Catadioptric adaptive camera for scenes of variable density of visual information

Ducrocq,

Caron,

Midavaine

et al. 2023

Appl. Opt.

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This paper presents the design method of a multi-resolution camera, named Visadapt. It is made of a conventional compact camera with a sensor and a lens pointed to a new deformable mirror so that the mirror in a flat state is parallel to the image plane. The main novelty of the latter mirror, to our knowledge, is the ability to control automatically strokes of several millimeters. This allows Visadapt to capture scenes with a spatially variable density of visual information. A grid of linear actuators, set underneath the mirror surface, deforms the mirror to reach the desired shape computed to capture several areas of different resolutions. Mechanical simulations are allowed to iterate on Visadapt’s design, to reduce the geometrical distortions in the images. Evaluations made on an actual prototype of Visadapt show that, by adapting the mirror shape, this camera can magnify a scene object up to 20%, even off-centered in the field-of-view, while still perceiving the rest of the scene.

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“…Such a system, called a catadioptric sensor (association of a mirror (catoptric) and lenses (dioptric)), has been widely studied in autonomous robotics [8][33] [6]. Its use for automotive applications has also been explored [18] [19] [27]. However, this sensor is not optimal for the monitoring of the surrounding environment because objects close to the vehicle may be occluded by the vehicle itself.…”

Section: Introductionmentioning

confidence: 99%

Road-line detection and 3D reconstruction using fisheye cameras

Boutteau¹,

Savatier²,

Bonardi³

et al. 2013

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

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In future Advanced Driver Assistance Systems (ADAS), smart monitoring of the vehicle environment is a key issue. Fisheye cameras have become popular as they provide a panoramic view with a few low-cost sensors. However, current ADAS systems have limited use as most of the underlying image processing has been designed for perspective views only. In this article we illustrate how the theoretical work done in omnidirectional vision over the past ten years can help to tackle this issue. To do so, we have evaluated a simple algorithm for road line detection based on the unified sphere model in real conditions. We firstly highlight the interest of using fisheye cameras in a vehicle, then we outline our method, we present our experimental results on the detection of lines on a set of 180 images, and finally, we show how the 3D position of the lines can be recovered by triangulation.

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Catadioptric vision system for an optimal observation of the driver face and the road scene

Cited by 3 publications

References 11 publications

A Survey on Adaptive Cameras

A Survey on Adaptive Cameras

Visadapt: Catadioptric adaptive camera for scenes of variable density of visual information

Road-line detection and 3D reconstruction using fisheye cameras

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