A four-step camera calibration procedure with implicit image correction

Heikkilä, Janne; Silvén, Olli

doi:10.1109/cvpr.1997.609468

Cited by 1,497 publications

(1,065 citation statements)

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“…D u , D v are the conversion factors from pixels to millimeters. See [12] for more details. We captured the images of a planar checkerboard pattern under various orientations (see figure 2).…”

Section: Geometric Calibrationmentioning

confidence: 99%

All the Images of an Outdoor Scene

Narasimhan

Wang

Nayar

2002

Lecture Notes in Computer Science

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Abstract. The appearance of an outdoor scene depends on a variety of factors such as viewing geometry, scene structure and reflectance (BRDF or BTF), illumination (sun, moon, stars, street lamps), atmospheric condition (clear air, fog, rain) and weathering (or aging) of materials. Over time, these factors change, altering the way a scene appears. A large set of images is required to study the entire variability in scene appearance. In this paper, we present a database of high quality registered and calibrated images of a fixed outdoor scene captured every hour for over 5 months. The dataset covers a wide range of daylight and night illumination conditions, weather conditions and seasons. We describe in detail the image acquisition and sensor calibration procedures. The images are tagged with a variety of ground truth data such as weather and illumination conditions and actual scene depths. This database has potential implications for vision, graphics, image processing and atmospheric sciences and can be a testbed for many algorithms. We describe an example application -image analysis in bad weather -and show how this method can be evaluated using the images in the database. The database is available online at http://www.cs.columbia.edu/CAVE/. The data collection is ongoing and we plan to acquire images for one year. Variability in Scene AppearanceThe appearance of a fixed scene depends on several factors -the viewing geometry, illumination geometry and spectrum, scene structure and reflectance (BRDF or BTF) and the medium (say, atmosphere) in which the scene is immersed. The estimation of one or more of these appearance parameters from one or more images of the scene has been an important part of research in computer vision. Several researchers have focused on solving this inverse problem under specific conditions of illumination (constant or smoothly varying), scene structure (no discontinuities), BRDF (lambertian) and transparent media (pure air). Images captured to evaluate their methods adhere to the specific conditions. While understanding each of these specific cases is important, modeling scene appearance in the most general setting is ultimately the goal of a vision system. To model, develop and evaluate such a general vision system, it is critical to collect a comprehensive set of images that describes the complete variability in the appearance of a scene. Several research groups have collected images of a scene (for example, faces, textures, objects) under varying lighting conditions

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Section: Geometric Calibrationmentioning

confidence: 99%

All the Images of an Outdoor Scene

Narasimhan

Wang

Nayar

2002

Lecture Notes in Computer Science

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“…see [3,[5][6][7][8]]. In the present application we used a freely available MATLAB Camera Calibration Toolbox developed by Bouguet [6].…”

Section: Lens Distortion Correctionmentioning

confidence: 99%

“…These common features, once introduced to Eq. (2), result in an over-specified system, permitting the selection of an optimal solution for the camera angles [for a detailed description see [5,6]] and COV through an iterative solver [Nelder-Mead simplex method, see [12]]. The present application aims to record the subject's amplitude and velocity of displacement.…”

Section: Stereo-triangulationmentioning

confidence: 99%

SVMT: A MATLAB toolbox for stereo-vision motion tracking of motor reactivity

Vousdoukas

Perakakis

Idrissi

et al. 2012

Computer Methods and Programs in Biomedicine

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ARTICLE IN PRESS No. of Pages 12 c o m p u t e r m e t h o d s a n d p r o g r a m s i n b i o m e d i c i n e x x x( 2 0 1 2 ) xxx-xxx j o u r n a l h o m e p a g e : w w w . i n t l . e l s e v i e r h e a l t h . IntroductionIn experimental psychophysiology, human motor reactivity to sensory stimulation is usually indexed by surface electromyography (EMG), which requires the placement of several electrodes on the skin surface [1]. This limits the mobility of the subject and reduces the possible contexts in which motor responses can be recorded and evaluated. In * Corresponding author. addition, EMG captures only the activity of specific muscle groups, whereas certain motor reflexes to sensory stimuli, such as the startle reflex, involve a global motor response characterized by complex muscle contraction patterns at different body areas [2]. A detailed investigation of these global motor reactivity patterns, in relation to underlying physiological control mechanisms, could result in a more systematic mapping of psychophysiological processes under sensory stimulation.0169-2607/$ -see front matter

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“…5 The prerequisite of this effective measurement is calibration to determine the internal camera geometric and optical characteristics, referred to as intrinsic camera parameters, which will be used in calculating the orientation of the probe with respect to the camera. A camera calibration toolbox, 6 developed based on previous work by Zhang 7 and Heikkila and Silven, 8 simplifies this task.…”

Section: Camera Calibrationmentioning

confidence: 99%

“…The transformation T v is included for convenience, to eliminate the need to construct a large voxel array that is mostly empty when the reconstructed volume is aligned with the camera coordinate system. 8 Only T m , ie., the transformation from the B-scan coordinate system to the marker coordinate system, and the estimates of s x and s y in Eq. 10 need to be solved.…”

Section: Three-dimensional Reconstruction Requirementsmentioning

confidence: 99%

Implementing Cost-effective 3-Dimensional Ultrasound Using Visual Probe Localization

Ali

Logeswaran

2007

J Digit Imaging

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This article proposes a set-up for a 3-dimensional ultrasound system using visual probe localization on the conventional 2-dimensional ultrasound machines readily available in most hospitals. A calibrated digital camera is used for probe-tracking (localization) purposes, whereas ultrasound probe calibration is implemented using a purpose-built phantom. The calibration steps and results are detailed here. The overall system is proven effective in clinical trials through scanning of human organs. Results obtained show successful, accurate 3-dimensional representations using this simple cost-effective set-up.

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A four-step camera calibration procedure with implicit image correction

Abstract: In

Cited by 1,497 publications

References 6 publications

All the Images of an Outdoor Scene

All the Images of an Outdoor Scene

SVMT: A MATLAB toolbox for stereo-vision motion tracking of motor reactivity

Implementing Cost-effective 3-Dimensional Ultrasound Using Visual Probe Localization

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