Acquisition of RGB-D images: methods

Stefańczyk, Maciej; Kornuta, Tomasz

doi:10.14313/par_203/82

Cited by 8 publications

(14 citation statements)

References 15 publications

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“…2. Szczegóły teoretyczne akwizycji oraz algorytmów przetwarzania obrazu z kamery RGBD są opisane w publikacjach [22][23][24][25][26]. Procesor wizyjny kamery Intel RealSense pozwala na bezpośrednie pobranie danych o głębi wyznaczonych na podstawie zrektyfikowanych obrazów z kamer podczerwieni wraz z korektą o dane z aktywnej stereowizji (za pomocą emitera IR).…”

Section: Cassieunclassified

Safety System for an Industrial Cooperating Robot Based on Depth Cameras

Masłowski¹,

Czubenko²

2019

PAR

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Section: Cassieunclassified

Safety System for an Industrial Cooperating Robot Based on Depth Cameras

Masłowski¹,

Czubenko²

2019

PAR

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“…Such a map can be -and often is -regarded as monochromatic (single-channel) image in which every point stores the distance to the particular object (part of the whole scene) in the direction indicated by a ray proceeding from an optical imaging device and passing through a particular pixel on the sensor (Stefańczyk & Kornuta, 2014). A more practical for further image analysis seems to be -accomplished by the appropriate conversion -assignment to each point of the image not a straightforward distance to the optical measuring device but a distance calculated in the direction perpendicular to the image sensor plane of the measuring device (or some other reference plane).…”

Section: Depth Maps and Point Cloudsmentioning

confidence: 99%

“…For example, dense maps are obtained by analyzing the entire image (or set of images) originating from the camera, and sparse maps are obtained by analyzing only some certain characteristic points e.g. vertices or edges (Stefańczyk & Kornuta, 2014).…”

Section: Depth Maps and Point Cloudsmentioning

confidence: 99%

“…Unfortunately in the case of a "disordered" point cloud, searching the neighbourhood around a particular point (this is usually a basic operation used in nearly all image analysis algorithms) is much more difficult. Hence, often to store this point cloud, there are used much more complex data structures (Stefańczyk & Kornuta, 2014).…”

Section: Depth Maps and Point Cloudsmentioning

confidence: 99%

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Laser Triangulation in 3-Dimensional Granulometric Analysis

Heyduk

2016

Archives of Mining Sciences

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LASER TRIANGULATION IN 3-DIMENSIONAL GRANULOMETRIC ANALYSIS TRIANGULACJA LASEROWA W TRÓJWYMIAROWYCH POMIARACH SKŁADU ZIARNOWEGOThe measurement of the particle size distribution plays an important role in mineral processing. Due to the high costs and time-consumption of the screening process, modern machine vision methods based on the acquisition and analysis of recorded photographic images. But the image analysis methods used so far, do not provide information on the three-dimensional shape of the grain. In the coal industry, the application scope of these methods is substantially limited by the low reflectivity of the black coal particle surface. These circumstances hinder proper segmentation of coal stream surface image. The limited information contained in two-dimensional image of the raw mineral stream surface, makes it difficult to identify proper size of grains partially overlapped by other particles and skewed particles. Particle height estimation based on the shadow length measurement becomes very difficult in industrial environment because of the fast movement of the conveyor belt and because of spatial arrangement of these particles, usually touching and overlapping. Method of laser triangulation connected with the movement of the conveyor belt makes it possible to create three-dimensional depth maps. Application of passive triangulation methods (e.g. stereovision) can be impeded because of the low contrast of the black coal on the black conveyor belt. This forces the use of active triangulation methods, directly identifying position of the analyzed image pixel. High contrast of the image can be obtained by a direct pointwise laser lighting. For the simultaneous identification of the entire section of the raw material stream it is useful to apply a linear laser (a planar sheet of the laser light). There have been presented basic formulas for conversion of pixel position on the camera CCD matrix to the real-word coordinates. A laboratory stand has been described. This stand includes a linear laser, two high-definition (2Mpix) cameras and stepper motor driver. The triangulation head moves on the rails along the belt conveyor section. There have been compared acquired depth maps and photographic images. Depth maps much better describe spatial arrangement of coal particles, and have a much lower noise level resulting from the specular light reflections from the shiny fragments of the particle surface. This makes possible an identification of the coal particles partially overlapped by other particles and obliquely arranged particles. It enables a partial elimination or compensation of image disturbances affecting the final result of the estimated particle size distribution. Because of the possibility of the reflected laser beam overriding by other particles it is advantageous to use a system of two cameras. Results of the experimental research confirmed the usefulness of the described method in spite of low reflectance factor of coal surface. The fast detection of changes in particle size distribution makes...

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“…W przypadku takich zastosowań można wymienić trzy główne metody pozyskiwania głębi: stereowizję, zastosowanie światła strukturalnego oraz pomiar czasu lotu wiązki. Podstawy fizyczne tych metod omówiono dokładnie w pierwszej części artykułu [25]. W drugiej części są omówione dostępne na rynku rozwiązania sprzętowe.…”

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Acquisition of RGB-D images: sensors

Kornuta¹,

Stefańczyk²

2014

PAR

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Zezwala się na korzystanie z artykułu na warunkach licencji Creative Commons Uznanie autorstwa 3.0 Streszczenie: Dwuczęściowy artykuł poświęcono czujnikom umożliwiającym akwizycję obrazów RGB-D. W pierwszej części uwagę skupiono na metodach akwizycji, w kolejnej części dokonano przeglądu czujników, zarówno dostępnych obecnie, jak i tych, które dopiero w najbliższym czasie pojawią się na rynku.

show abstract

Acquisition of RGB-D images: methods

Cited by 8 publications

References 15 publications

Safety System for an Industrial Cooperating Robot Based on Depth Cameras

Safety System for an Industrial Cooperating Robot Based on Depth Cameras

Laser Triangulation in 3-Dimensional Granulometric Analysis

Acquisition of RGB-D images: sensors

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