In this paper, we propose a Charuco board-based omnidirectional camera calibration method to solve the problem of conventional methods requiring overly complicated calibration procedures. Specifically, the proposed method can easily and precisely provide two-dimensional and three-dimensional coordinates of patterned feature points by arranging the omnidirectional camera in the Charuco board-based cube structure. Then, using the coordinate information of the feature points, an intrinsic calibration of each camera constituting the omnidirectional camera can be performed by estimating the perspective projection matrix. Furthermore, without an additional calibration structure, an extrinsic calibration of each camera can be performed, even though only part of the calibration structure is included in the captured image. Compared to conventional methods, the proposed method exhibits increased reliability, because it does not require additional adjustments to the mirror angle or the positions of several pattern boards. Moreover, the proposed method calibrates independently, regardless of the number of cameras comprising the omnidirectional camera or the camera rig structure. In the experimental results, for the intrinsic parameters, the proposed method yielded an average reprojection error of 0.37 pixels, which was better than that of conventional methods. For the extrinsic parameters, the proposed method had a mean absolute error of 0.90° for rotation displacement and a mean absolute error of 1.32 mm for translation displacement.
In this paper, a photosensor-based latency measurement system for head-mounted displays (HMDs) is proposed. The motion-to-photon latency is the greatest reason for motion sickness and dizziness felt by users when wearing an HMD system. Therefore, a measurement system is required to accurately measure and analyze the latency to reduce these problems. The existing measurement system does not consider the actual physical movement in humans, and its accuracy is also very low. However, the proposed system considers the physical head movement and is highly accurate. Specifically, it consists of a head position model-based rotary platform, pixel luminance change detector, and signal analysis and calculation modules. Using these modules, the proposed system can exactly measure the latency, which is the time difference between the physical movement for a user and the luminance change of an output image. In the experiment using a commercial HMD, the latency was measured to be up to 47.05 ms. In addition, the measured latency increased up to 381.17 ms when increasing the rendering workload in the HMD.
Because the interest in virtual reality (VR) has increased recently, studies on head-mounted displays (HMDs) have been actively conducted. However, HMD causes motion sickness and dizziness to the user, who is most affected by motion-to-photon latency. Therefore, equipment for measuring and quantifying this occurrence is very necessary. This paper proposes a novel system to measure and visualize the time sequential motion-to-photon latency in real time for HMDs. Conventional motion-to-photon latency measurement methods can measure the latency only at the beginning of the physical motion. On the other hand, the proposed method can measure the latency in real time at every input time. Specifically, it generates the rotation data with intensity levels of pixels on the measurement area, and it can obtain the motion-to-photon latency data in all temporal ranges. Concurrently, encoders measure the actual motion from a motion generator designed to control the actual posture of the HMD device. The proposed system conducts a comparison between two motions from encoders and the output image on a display. Finally, it calculates the motion-to-photon latency for all time points. The experiment shows that the latency increases from a minimum of 46.55 ms to a maximum of 154.63 ms according to the workload levels.
In this work, airborne brake wear particulate matter (PM) emissions from a brake system were investigated by time-resolved and temperature-dependent measurement using a dynamometer. The measurement was performed for representative friction materials, 3 low-steel (LS) and 4 non-steel (NS), which are currently in worldwide use. The PM emission factor was found to be varied as large as by one order of magnitude depending on the composition of friction materials(pads). The airborne particle mass emissions from the LS materials ranged from 1.88 to 3.14 mg/km/vehicle, while the emissions from the NS ranged from 0.3 to 2.34 mg/km/vehicle, which is, in general, smaller than the LS. The time-resolved data imply that particle emissions in the extra-high-speed region of the WLTC cycle, where friction occurs at high temperature (T disk > 150 °C), is much higher than in the low-speed region, and determines the total PM mass emission factor. It was found that the friction materials containing metals such as Cu and Sn (LS-2/-3 and NS-4/-5) exhibited a lower PM emission factor. This result suggests that copper and tin, which forms an effective lubricating tribolayer in the interface between the pad and disk at high temperature, remarkably reduces PM emissions. It has been also found that the surface roughness of worn brake pads is positively proportional to PM emissions according to surface topography analysis, which is consistent with composition effect. These findings suggest that tribological engineering to provide sliding frictional behavior at elevated temperature is crucial to reducing PM emissions.
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