Single Color Camera Research Articles

Improvement in the Number of Velocity Vector Acquisitions Using an In-Picture Tracking Method for 3D3C Rainbow Particle Tracking Velocimetry

Particle image velocimetry and particle tracking velocimetry (PTV) have developed from two-dimensional two-component (2D2C) velocity vector measurements to 3D3C measurements. Rainbow particle tracking velocimetry is a low-cost 3D3C measurement technique adopting a single color camera. However, the vector acquisition rate is not so high. To increase the number of acquired vectors, this paper proposes a high probability and long-term tracking method. First, particles are tracked in a raw picture instead of in three-dimensional space. The tracking is aided by the color information. Second, a particle that temporarily cannot be tracked due to particle overlap is compensated for using the positional information at times before and after. The proposed method is demonstrated for flow under a rotating disk with different particle densities and velocities. The use of the proposed method improves the tracking rate, number of continuous tracking steps, and number of acquired velocity vectors. The method can be applied under the difficult conditions of high particle density (0.004 particles per pixel) and large particle movement (maximum of 60 pix).

A Single-Camera-Based Three-Dimensional Velocity Field Measurement Method for Granular Media in Mass Finishing with Deep Learning.

Surface treatment processes such as mass finishing play a crucial role in enhancing the quality of machined parts across industries. However, accurate measurement of the velocity field of granular media in mass finishing presents significant challenges. Existing measurement methods suffer from issues such as complex and expensive equipment, limited to single-point measurements, interference with the flow field, and lack of universality in different scenarios. This study addresses these issues by proposing a single-camera-based method with deep learning to measure the three-dimensional velocity field of granular flow. We constructed a complete measurement system and analyzed the accuracy and performance of the proposed method by comparing the measurement results with those of the traditional DIC algorithm. The results show that the proposed method is very accurate in measuring spatial displacement, with an average error of less than 0.07 mm and a calculation speed that is 1291.67% of the traditional DIC algorithm under the same conditions. Additionally, experiments in a bowl-type vibratory finishing machine demonstrate the feasibility of the proposed method in capturing the three-dimensional flow of granular media. This research not only proposed a novel method for three-dimensional reconstruction and velocity field measurement using a single-color camera, but also demonstrated a way to combine deep learning with traditional optical techniques. It is of great significance to introduce deep learning to improve traditional optical techniques and apply them to practical engineering measurements.

A single‐camera telecentric imaging stereo‐digital image correlation system and its application to carotid pulse signal detection

AbstractCarotid pulse signal (CPS) is one of the most important biomarkers for evaluating cardiovascular risk. To realize easy‐to‐operate and accurate CPS detection, a single‐camera telecentric imaging stereo‐digital image correlation (stereo‐DIC) system is established. The system uses a specially designed colour separation device and a single colour camera attached with a telecentric lens to record images of blue and red colours from different optical paths. By processing the recorded two sub‐channel colour images using regular stereo‐DIC algorithm, full‐field 3D displacements of the skin on the neck directly over the carotid artery are obtained. The maximum fluctuations in the out‐of‐plane displacement direction are extracted as CPS, based on which velocity, acceleration and frequency can be further extracted. The performance of the established system was demonstrated by detecting the pulse signal of a volunteer before and after exercise.

Three-Dimensional Shape and Deformation Measurements Based on Fringe Projection Profilometry and Fluorescent Digital Image Correlation via a 3 Charge Coupled Device Camera.

We propose a novel hybrid FPP-DIC technique to measure an object's shape and deformation in 3D simultaneously by using a single 3CCD color camera, which captures the blue fringe patterns and red fluorescent speckles within the same image. Firstly, red fluorescent speckles were painted on the surface of the specimen. Subsequently, 12 computer-generated blue fringe patterns with a black background were projected onto the surface of the specimen using a DLP projector. Finally, both the reference and deformed images with three different frequencies and four shifted phases were captured using a 3CCD camera. This technique employed a three-chip configuration in which red-green-blue chips were discretely integrated in the 3CCD color camera sensor, rendering independent capture of RGB information possible. Measurement of out-of-plane displacement was carried out through the implementation of Fringe Projection Profilometry (FPP), whereas the in-plane displacement was evaluated using a 2D Digital Image Correlation (DIC) method by leveraging a telecentric-lens-based optical system. In comparison to the traditional FPP-DIC hybrid methodology, the present approach showed a lower incidence of crosstalk between the fringe patterns and speckle patterns while also offering a corrective for the coupling of the in-plane displacement and out-of-plane displacement. Experimental results for the in-plane cantilever beam and out-of-plane disk comparisons with the traditional 3D-DIC method indicated that the maximum discrepancy obtained between FPP-DIC and 3D-DIC was 0.7 μm and 0.034 mm with different magnifications, respectively, validating the effectiveness and precision of the novel proposed FPP-DIC method.

Simultaneous PIV-LIF Measurements With A SCMOS Color Camera Using RuPhen

Simultaneous velocity and temperature measurements are important in understanding the heat and momentum transfer in thermal fluid flow applications. PIV measures the displacement of a constellation of tracer particles using cross-correlation to obtain the velocity field, while LIF uses temperature-dependent fluorescence emission to map the intensity to temperature using a calibration. In this work, we present a low-cost PIV-LIF system to simultaneously measure velocity and temperature fields in aqueous flows with a single color camera, a CW laser (λe = 465 nm) and a novel dye RuPhen. The technique can also be extended to 3D LIF/3D2C PIV using a scanning light sheet. We find that the RuPhen dye is well-suited due to its peak absorption in the blue, emission in the red, and a strong temperature-dependent emission with a sensitivity coefficient of -4%/ °C. We also propose a method to use the red and green channels to correct for any laser power fluctuations. We demonstrate the technique by studying the flow past and inside a heated hollow hemisphere in a small water tunnel.

Discrimination and Measurement of Droplet and Ice Crystal by Combining Digital Inline Holography With Interferometric Particle Imaging With Single Color Camera

The discrimination and measurement of complex particle field mixing spherical liquid droplets and other solid irregular particles are challenging but of significance in industry, e.g., droplets and ice crystals in icing wind tunnel or in mixing phase cloud during airplane icing flight test. An approach is proposed by combining digital inline holography (DIH) and interferometric particle imaging (IPI) techniques, and a setup is elaborately designed by using a color camera to simultaneously record DIH and IPI signals of the same droplet/ice crystal in the red and green channels of a RGB image respectively. Water droplets and ice crystals generated in a cooling chamber are experimentally tested. Results show that IPI signals tune from regular interferometric fringes to random speckles as water droplet converts to ice crystal, and it is an obvious and robust indicator to discriminate water droplet and ice crystal. Water droplet sizes in the range from 100 μm to 300 μm measured by DIH and IPI coincide with each other, with relative deviations within ±5%. Concerning ice crystal, the 2D Fourier transform of IPI speckle pattern agrees well in both overall shape and size with the 2D autocorrelation of DIH reconstructed in-focus image, with size discrepancy within 10%. With the capability of phase discrimination and size and shape measurement, the proposed method combing DIH and IPI has the potential to be instrumented and applied to cloud particle fields.

High-Resolution Melt Pool Thermal Imaging for Metals Additive Manufacturing Using the Two-Color Method with a Single Color Camera

High-Resolution Melt Pool Thermal Imaging for Metals Additive Manufacturing Using the Two-Color Method with a Single Color Camera

Dual-plane ensemble correlation for pixelwise 2D-3C velocity field measurements using a single camera

As an extension of single-pixel particle image velocimetry (SP-PIV), a novel method to determine both the out-of-plane and in-plane velocity fields with single-pixel resolution is presented. With this approach, called dual-plane SP-PIV, mean velocity vector fields with three components (3C) can be measured with single-pixel resolution using a single-color camera and two differently colored laser sheets. The method computes the ensemble correlation across two planes illuminated simultaneously by the two laser sheets. The method is demonstrated via an experiment in which a rotating flow is induced by an impeller. The method is validated by comparing its results with those of conventional PIV. The results show good accordance in terms of the magnitudes and spatial distributions of the out-of-plane velocities and provide a new approach to 3C velocity field measurements with high spatial resolution.

PhysCap

Marker-less 3D human motion capture from a single colour camera has seen significant progress. However, it is a very challenging and severely ill-posed problem. In consequence, even the most accurate state-of-the-art approaches have significant limitations. Purely kinematic formulations on the basis of individual joints or skeletons, and the frequent frame-wise reconstruction in state-of-the-art methods greatly limit 3D accuracy and temporal stability compared to multi-view or marker-based motion capture. Further, captured 3D poses are often physically incorrect and biomechanically implausible, or exhibit implausible environment interactions (floor penetration, foot skating, unnatural body leaning and strong shifting in depth), which is problematic for any use case in computer graphics. We, therefore, present PhysCap , the first algorithm for physically plausible, real-time and marker-less human 3D motion capture with a single colour camera at 25 fps. Our algorithm first captures 3D human poses purely kinematically. To this end, a CNN infers 2D and 3D joint positions, and subsequently, an inverse kinematics step finds space-time coherent joint angles and global 3D pose. Next, these kinematic reconstructions are used as constraints in a real-time physics-based pose optimiser that accounts for environment constraints ( e.g. , collision handling and floor placement), gravity, and biophysical plausibility of human postures. Our approach employs a combination of ground reaction force and residual force for plausible root control, and uses a trained neural network to detect foot contact events in images. Our method captures physically plausible and temporally stable global 3D human motion, without physically implausible postures, floor penetrations or foot skating, from video in real time and in general scenes. PhysCap achieves state-of-the-art accuracy on established pose benchmarks, and we propose new metrics to demonstrate the improved physical plausibility and temporal stability.

Two-color, two-dimensional pyrometers based on monochrome and color cameras for high-temperature (>1000 K) planar measurements.

Two high-temperature 2D-pyrometers are described in this work. They are, respectively, based on the comparison of light intensities received by two monochrome cameras with narrow filters and the different color channels in a single color camera. The calibration procedure includes tests with thermocouples in flame flue gases and with a light bulb filament in the range 1050 K-2650 K, although the upper limit may be reliably extrapolated in the two-camera pyrometer. This device shows smaller uncertainties in absolute temperature determination than the other, ∼±15 K in the calibration curve. A combination of the two-color technique with intensity pyrometry is shown to allow the quantification of differences of the order of 1 K for uniform emissivity surfaces. Several examples of application of both pyrometers are presented to assess their spatial resolution and thermal capabilities, including the contact between the hot filament and its support in the light bulb and fine-wire thermocouples with large bead/wire ratios. The optical systems were designed for their use at short working distances and with high spatial resolution (4.7 μm/pixel and 8.7 µm/pixel) but could be adapted to other scenarios.

Grazing incidence polarized light imaging of footwear prints

Footwear prints are important evidence in criminal investigation. They represent changes in the surface morphology due to disturbance to fine particle distributions. Existing non-contact optical detection methods usually measure the light intensity contrasts between the footwear prints and the ground, which can be enhanced by grazing incident illumination. We take polarization images of footwear prints on different types of floors using a commercial single lens reflex color camera. Results show that adding linear polarizers in front of the camera lens and light source improves the contrast of footwear print images. The best contrasts are achieved in degree of linear polarization. In addition, the three-color channels of the camera can be used to examine the spectral features of the polarization images. According to the experimental results, the best contrast is obtained at the blue channel. The current work shows that grazing incidence polarized light imaging can effectively enhance the contrast of the footwear prints against the floors, which would help obtain footwear evidence in criminal investigation.

A Cost-Effective Single-Shot Structured Light System for 3D Shape Measurement

Single-shot three-dimensional (3D) shape measurement techniques have attracted extensive researches, as they are suitable for dynamic measurement. In this study, a cost-effective single-shot structured light system (CES-SLS) is proposed for 3D shape measurement by using a color camera and a normal projector. With the aid of two planar mirrors and an isosceles right-angle mirror, a single color camera functions as a binocular vision. A single-shot color random speckle pattern (CRSP) is used to encode the object by the normal projector. The dense corresponding points (DCP) are derived by the spatial-temporal correlation of RGB image subsets instead of the spatial correlation of gray image subsets in the conventional method. An inverse compositional Gaussian Newton (IC-GN) iteration method with the second-order shape function is then introduced to find the sub-pixel corresponding points (CP). Furthermore, a geometrical 3D recovery method is presented to calculate the 3D point by minimizing the re-projection error. The experimental results demonstrate the comparative advantages of the proposed CES-SLS against the system using a single-shot random speckle pattern (RSP) and the curve fitting sub-pixel method in the aspects of measurement accuracy and noise robustness. In addition, the re-projection error of each 3D point from the geometrical method is smaller than that of the conventional mid-point.

Time-resolved temperature characterization of a hypersonic shock layer using a single high-speed color camera for aerospace design applications

Two-color ratio pyrometry (TCRP) using a high-speed color camera has been used for temperature characterization of a hypersonic shock layer. The camera, used as a pyrometer, was calibrated in-house using a monochromator to determine its spectral responsivity and was used to acquire time-resolved images of the flow field over test models at a frame rate of 20 000 fps to understand the evolution of temperature inside the shock region. The optical efficiency of the monochromator and other optical equipment were determined separately and corrected for. Two test models, a flat-faced cylinder of diameter 70 mm and a hemisphere of diameter 80 mm, were used for the experiments to study the effect of geometry on the results. Experiments were performed in a free-piston-driven shock tunnel at a stagnation enthalpy of 5.2 MJ kg−1. The average steady-state temperature in the stagnation region in the cylinder was about 3650 K ± 3% (uncertainty in the shock layer due to camera noise), and for the hemisphere it was 3300 K ± 6%. The resolved temperature was 14% higher than that obtained from a similar, but time-integrated, measurement obtained using a digital single lens reflex (DSLR) camera. Steady 2D numerical simulations were performed to reconstruct the 3D flow assuming azimuthal symmetry, and an algorithm was developed to use the shape of the temperature profile along the line-of-sight (LOS) derived from simulations to predict the actual stagnation-plane temperature from the experimental LOS-integrated TCRP-derived temperature. The actual temperature in the stagnation region on the vertical plane of symmetry (stagnation plane) for the cylinder and the hemisphere were higher by 2.76% and 1.77%, respectively, than the corresponding TCRP-derived LOS-integrated temperature. The results are promising for future use in determining intense temperature gradients and heat flux in the vicinity of space vehicles and for the design of efficient thermal protection systems.

Single‐camera special stereo‐digital image correlation applied for accurate virtual fields method identification

AbstractA single‐camera special stereo‐DIC (SS‐DIC) is proposed for accurate virtual fields method (VFM) identification. The single‐camera SS‐DIC allows accurate surface 3D deformation measurements using a single colour camera and a specially designed colour separation device. It not only effectively eliminates the unavoidable out‐of‐plane movement/rotation due to unideal in‐plane loading but also delivers uniformly distributed measurement points that brings great simplicity and convenience for internal virtual work calculation in VFM. In addition, since only a single camera is used for stereovision, the proposed SS‐DIC system requires no complicated synchronisation devices. The effectiveness and practicality of the proposed method are evaluated by heterogeneous deformation experiments of a holed aluminium alloy and 304 stainless steel plate. Combined with a high‐speed colour camera, the proposed method is expected to be a simple and practical method for the calibration of material constitutive model under intermediate and high strain rate conditions using VFM.

A flexible and easy-to-implement single-camera microscopic 3D digital image correlation technique

We propose a novel, flexible and easy-to-implement single-camera microscopic three-dimensional digital image correlation (3D-DIC) technique for accurate full-field shape, motion and deformation measurements at the microscale. The established microscopic 3D-DIC system comprises a single 3CCD color camera, a high-magnification zoom lens, and a specially designed color separation device using a beam splitter, two optical bandpass filters and three plane mirrors. To perform accurate stereo measurement, color images of a test sample surface are recorded by the 3CCD camera, which observes the test sample via the microscopic imaging system from two different optical paths with the aid of the color separation device. The recorded color images can be subsequently separated to red and green channel sub-images which constitute stereo pairs corresponding to different perspectives. The separated stereo pairs can be subsequently analyzed using regular 3D-DIC to extract full-field 3D shape and deformation of the test object surface. The method was first validated by a series of benchmark tests, involving the 3D shape reconstruction of steel balls with different diameters, in-plane and out-of-plane translation tests. Surface 3D deformation measurement of a planar acrylic plate with micro-features was also performed to show the practicality of the proposed method. This method provides new simple and practical avenues for performing shape and deformation measurement at microscale, showing great potential in both material testing and bio-tissue characterization.

Scaled layout recovery with wide field of view RGB-D

In this work, we propose a method that integrates depth and fisheye cameras to obtain a wide 3D scene reconstruction with scale in one single shot. The motivation of such integration is to overcome the narrow field of view in consumer RGB-D cameras and lack of depth and scale information in fisheye cameras. The hybrid camera system we use is easy to build and calibrate, and currently consumer devices with similar configuration are already available in the market. With this system, we have a portion of the scene with shared field of view that provides simultaneously color and depth. In the rest of the color image we estimate the depth by recovering the structural information of the scene. Our method finds and ranks corners in the scene combining the extraction of lines in the color image and the depth information. These corners are used to generate plausible layout hypotheses, which have real-world scale due to the usage of depth. The wide angle camera captures more information from the environment (e.g. the ceiling), which helps to overcome severe occlusions. After an automatic evaluation of the hypotheses, we obtain a scaled 3D model expanding the original depth information with the wide scene reconstruction. We show in our experiments with real images from both home-made and commercial systems that our method achieves high success ratio in different scenarios and that our hybrid camera system outperforms the single color camera set-up while additionally providing scale in one single shot.

Large-scale multiview 3D hand pose dataset

Accurate visual hand pose estimation at joint level has several applications for human-robot interaction, natural user interfaces and virtual/augmented reality applications. However, it is still an open problem being addressed by the computer vision community. Recent novel deep learning techniques may help circumvent the limitations of standard approaches. However, they require large amounts of accurate annotated data.Hand pose datasets that have been released so far present issues such as limited number of samples, inaccurate data or high-level annotations. Moreover, most of them are focused on depth-based approaches, providing only depth information (missing RGB data).In this work, we present a novel multiview hand pose dataset in which we provide hand color images and different kind of annotations for each sample, i.e. the bounding box and the 2D and 3D location on the joints in the hand. Furthermore, we introduce a simple yet accurate deep learning architecture for real-time robust 2D hand pose estimation. Then, we conduct experiments that show how the use of the proposed dataset in the training stage produces accurate results for 2D hand pose estimation using a single color camera.

LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System

Collision avoidance is a critical task in many applications, such as ADAS (advanced driver-assistance systems), industrial automation and robotics. In an industrial automation setting, certain areas should be off limits to an automated vehicle for protection of people and high-valued assets. These areas can be quarantined by mapping (e.g., GPS) or via beacons that delineate a no-entry area. We propose a delineation method where the industrial vehicle utilizes a LiDAR (Light Detection and Ranging) and a single color camera to detect passive beacons and model-predictive control to stop the vehicle from entering a restricted space. The beacons are standard orange traffic cones with a highly reflective vertical pole attached. The LiDAR can readily detect these beacons, but suffers from false positives due to other reflective surfaces such as worker safety vests. Herein, we put forth a method for reducing false positive detection from the LiDAR by projecting the beacons in the camera imagery via a deep learning method and validating the detection using a neural network-learned projection from the camera to the LiDAR space. Experimental data collected at Mississippi State University’s Center for Advanced Vehicular Systems (CAVS) shows the effectiveness of the proposed system in keeping the true detection while mitigating false positives.

3D digital image correlation using a single 3CCD colour camera and dichroic filter

In recent years, three-dimensional digital image correlation methods using a single colour camera have been reported. In this study, we propose a simplified system by employing a dichroic filter (DF) to replace the beam splitter and colour filters. The DF can be used to combine two views from different perspectives reflected by two planar mirrors and eliminate their interference. A 3CCD colour camera is then used to capture two different views simultaneously via its blue and red channels. Moreover, the measurement accuracy of the proposed method is higher since the effect of refraction is reduced. Experiments are carried out to verify the effectiveness of the proposed method. It is shown that the interference between the blue and red views is insignificant. In addition, the measurement accuracy of the proposed method is validated on the rigid body displacement. The experimental results demonstrate that the measurement accuracy of the proposed method is higher compared with the reported methods using a single colour camera. Finally, the proposed method is employed to measure the in- and out-of-plane displacements of a loaded plastic board. The re-projection errors of the proposed method are smaller than those of the reported methods using a single colour camera.

A Single Color Camera Stereo Vision System

In this paper, a novel single color camera stereo vision system is proposed. Two planar mirrors are used to create double views (blue and red views). A dichroic filter (DF) is used to combine them and eliminate their interference. The double views can then be captured by a color camera through blue and red channels. When the DF transmits the red light, refraction would occur. During calibration, we separate the calibration process: calibrate the virtual red camera and the virtual blue camera in order, and then calibrate their pose relationship. The refraction is removed in this process. Moreover, when computing the 3-D position of a point, the measurement error caused by the refraction is also considered. In this experiment, the interference between the blue- and red-channels is shown to be negligible. We verified the proposed vision system on the standard spherical and cylindrical surfaces. It is shown that the measurement accuracy is improved when the effect of refraction is considered. In addition, the noise robustness of this proposed system is also tested. The measurement accuracy would not be affected severely, if the standard deviation of the uniformly distributed random noise is less than 0.035. Finally, the proposed system is employed to measure the profile of a flower model. The proposed system has potential industrial applications.