Event cameras output asynchronous events to represent intensity changes with a high temporal resolution, even under extreme lighting conditions. Currently, most of the existing works use a single contrast threshold to estimate the intensity change of all pixels. However, complex circuit bias and manufacturing imperfections cause biased pixels and mismatch contrast threshold among pixels, which may lead to undesirable outputs. In this paper, we propose a new event camera model and two calibration approaches which cover event-only cameras and hybrid image-event cameras. When intensity images are simultaneously provided along with events, we also propose an efficient online method to calibrate event cameras that adapts to time-varying event rates. We demonstrate the advantages of our proposed methods compared to the state-of-the-art on several different event camera datasets.
Australian Institute for Machine Learning（澳大利亚机器学习研究所）；University of Adelaide（阿德莱德大学）；Singapore Management University（新加坡管理大学）
State-of-the-art (SOTA) anomaly segmentation approaches on complex urban driving scenes explore pixel-wise classification uncertainty learned from outlier exposure, or external reconstruction models. However, previous uncertainty approaches that directly associate high uncertainty to anomaly may sometimes lead to incorrect anomaly predictions, and external reconstruction models tend to be too inefficient for real-time self-driving embedded systems. In this paper, we propose a new anomaly segmentation method, named pixel-wise energy-biased abstention learning (PEBAL), that explores pixel-wise a…
Tokyo Institute of Technology（东京工业大学）；Microsoft STCA（微软STCA）；Nanjing University（南京大学）；Microsoft Research Asia（微软亚洲研究院）
The long-tailed class distribution in visual recognition tasks poses great challenges for neural networks on how to handle the biased predictions between head and tail classes, i.e., the model tends to classify tail classes as head classes. While existing research focused on data resampling and loss function engineering, in this paper, we take a different perspective: the classification margins. We study the relationship between the margins and logits (classification scores) and empirically observe the biased margins and the biased logits are positively correlated. We propose MARC, a simple ye…
Semantic segmentation is the task of assigning a class-label to each pixel in an image. We propose a region-based semantic segmentation framework which handles both full and weak supervision, and addresses three common problems: (1) Objects occur at multiple scales and therefore we should use regions at multiple scales. However, these regions are overlapping which creates conflicting class predictions at the pixel-level. (2) Class frequencies are highly imbalanced in realistic datasets. (3) Each pixel can only be assigned to a single class, which creates competition between classes. We address…
University of South Bohemia in České Budějovice（南波希米亚大学）
In this paper, we introduce a novel - physico-chemical - approach for calibration of a digital camera chip. This approach utilizes results of measurement of incident light spectra of calibration films of different levels of gray for construction of calibration curve (number of incident photons vs. image pixel intensity) for each camera pixel. We show spectral characteristics of such corrected digital raw image files (a primary camera signal) and demonstrate their suitability for next image processing and analysis.
Accurately calibrating light field camera is essential to its applications. Rapid progress has been made in this area in the past decades. In this paper, detailed analysis was first performed towards the state of the art projection models for calibration which were further interpreted in three representations, including the correspondence between rays and pixels, 3D physical points and pixels and between 3D physical points and 3D signal structure of the captured light field. Based on the analysis, parameters in the projection model were grouped into direction parameter set and depth parameter …
University of Nevada, Reno（内华达大学雷诺分校）；NTNU - Norwegian University of Science and Technology（挪威科技大学）
This report accompanies a dataset release on visual and thermal camera data and details a procedure followed to align such multi-modal camera frames in order to provide pixel-level correspondence between the two without using intrinsic or extrinsic calibration information. To achieve this goal we benefit from progress in the domain of multi-modal image alignment and specifically employ the Mattes Mutual Information Metric to guide the registration process. In the released dataset we release both the raw visual and thermal camera data, as well as the aligned frames, alongside calibration parame…
Ruhr West University of Applied Sciences（鲁尔西部应用科学大学）；Visteon Electronics GmbH（伟世通电子有限公司）
Unbiased confidence estimates of neural networks are crucial especially for safety-critical applications. Many methods have been developed to calibrate biased confidence estimates. Though there is a variety of methods for classification, the field of object detection has not been addressed yet. Therefore, we present a novel framework to measure and calibrate biased (or miscalibrated) confidence estimates of object detection methods. The main difference to related work in the field of classifier calibration is that we also use additional information of the regression output of an object detecto…
Technical University of Denmark（丹麦技术大学）；University of Southern Denmark（南丹麦大学）
The most prevalent routine for camera calibration is based on the detection of well-defined feature points on a purpose-made calibration artifact. These could be checkerboard saddle points, circles, rings or triangles, often printed on a planar structure. The feature points are first detected and then used in a nonlinear optimization to estimate the internal camera parameters.We propose a new method for camera calibration using the principle of inverse rendering. Instead of relying solely on detected feature points, we use an estimate of the internal parameters and the pose of the calibration …
End-to-End QGAN-Based Image Synthesis via Neural Noise Encoding and Intensity Calibration
Shanghai Maritime University（上海海洋大学）；Agency for Science, Technology and Research（科技研究局）；Singapore University of Technology and Design（新加坡科技设计大学）；Institute of High Performance Computing（高性能计算研究院）
Compared with raw images, the more common JPEG images are less useful for machine vision algorithms and professional photographers because JPEG-sRGB does not preserve a linear relation between pixel values and the light measured from the scene. A camera is said to be radiometrically calibrated if there is a computational model which can predict how the raw linear sensor image is mapped to the corresponding rendered image (e.g. JPEGs) and vice versa. This paper begins with the observation that the rank order of pixel values are mostly preserved post colour correction. We show that this observat…
The University of Tokyo（东京大学）；Tokyo Institute of Technology（东京工业大学）
We propose a spatial calibration method for wide Field-of-View (FoV) Near-Eye Displays (NEDs) with complex image distortions. Image distortions in NEDs can destroy the reality of the virtual object and cause sickness. To achieve distortion-free images in NEDs, it is necessary to establish a pixel-by-pixel correspondence between the viewpoint and the displayed image. Designing compact and wide-FoV NEDs requires complex optical designs. In such designs, the displayed images are subject to gaze-contingent, non-linear geometric distortions, which explicit geometric models can be difficult to repre…
Universidad Politécnica de Madrid（马德里理工大学）；Universidad Complutense de Madrid（马德里康普顿斯大学）
In 3D reconstruction, the recovery of the calibration parameters of the cameras is paramount since it provides metric information about the observed scene, e.g., measures of angles and ratios of distances. Autocalibration enables the estimation of the camera parameters without using a calibration device, but by enforcing simple constraints on the camera parameters. In the absence of information about the internal camera parameters such as the focal length and the principal point, the knowledge of the camera pixel shape is usually the only available constraint. Given a projective reconstruction…
University of Michigan（密歇根大学）；Adobe Research（奥多比研究院）
Geometric camera calibration is often required for applications that understand the perspective of the image. We propose perspective fields as a representation that models the local perspective properties of an image. Perspective Fields contain per-pixel information about the camera view, parameterized as an up vector and a latitude value. This representation has a number of advantages as it makes minimal assumptions about the camera model and is invariant or equivariant to common image editing operations like cropping, warping, and rotation. It is also more interpretable and aligned with huma…
LenghuSky-8: An 8-Year All-Sky Cloud Dataset with Star-Aware Masks and Alt-Az Calibration for Segmentation and Nowcasting
State Key Laboratory of Dark Matter Physics, Tsung-Dao Lee Institute & School of Physics and Astronomy, Shanghai Jiao Tong University（暗物质物理国家重点实验室、李政道研究所及物理天文学院、上海交通大学）；National Astronomical Observatories, Chinese Academy of Sciences（中国科学院国家天文台）；School of Computer Technology and Application, Qinghai University（青海大学计算机技术与应用学院）
High-precision visual navigation device calibration method based on collimator
College of Aerospace Science and Engineering, National University of Defense Technology（国防科技大学航天科学与工程学院）；North Navigation Control Technology Co., Ltd（北方导航控制技术股份有限公司）
Electronics and Telecommunications Research Institute (ETRI)（电子通信研究院（ETRI））
In this paper, we present a novel zero-shot camera calibration method that estimates camera parameters with no calibration image. It is common sense that we need at least one or more pattern images for camera calibration. However, the proposed method estimates camera parameters from the horizontal and vertical field of view information of the camera without any image acquisition. The proposed method is particularly useful for wide-angle or fisheye cameras that have large image distortion. Image distortion is modeled in the way fisheye lenses are designed and estimated based on the square pixel…
