In many computer vision domains, the input images must conform with the pinhole camera model, where straight lines in the real world are projected as straight lines in the image. Performing computer vision tasks on live sports broadcast footage imposes challenging requirements where the algorithms cannot rely on a specific calibration pattern must be able to cope with unknown and uncalibrated cameras, radial distortion originating from complex television lenses, few visual clues to compensate distortion by, and the necessity for real-time performance. We present a novel method for single-image automatic lens distortion compensation based on deep convolutional neural networks, capable of real-time performance and accuracy using two highest-order coefficients of the polynomial distortion model operating in the application domain of sports broadcast. Keywords: Deep Convolutional Neural Network, Radial Distortion, Single Image Rectification
This paper presents a blind detection and compensation technique for camera lens geometric distortions. The lens distortion introduces higher-order correlations in the frequency domain and in turn it can be detected using higher-order spectral analysis tools without assuming any specific calibration target. The existing blind lens distortion removal method only considered a single-coefficient radial distortion model. In this paper, two coefficients are considered to model approximately the geometric distortion. All the models considered have analytical closed-form inverse formulae.
Isfahan University of Technology（伊斯法罕理工大学）；University of Michigan（密歇根大学）
Reversible image watermarking guaranties restoration of both original cover and watermark logo from the watermarked image. Capacity and distortion of the image under reversible watermarking are two important parameters. In this study a reversible watermarking is investigated with focusing on increasing the embedding capacity and reducing the distortion in medical images. Integer wavelet transform is used for embedding where in each iteration, one watermark bit is embedded in one transform coefficient. We devise a novel approach that when a coefficient is modified in an iteration, the produced …
Our aim is to estimate the perspective-effected geometric distortion of a scene from a video feed. In contrast to all previous work we wish to achieve this using from low-level, spatio-temporally local motion features used in commercial semi-automatic surveillance systems. We: (i) describe a dense algorithm which uses motion features to estimate the perspective distortion at each image locus and then polls all such local estimates to arrive at the globally best estimate, (ii) present an alternative coarse algorithm which subdivides the image frame into blocks, and uses motion features to deriv…
Tokyo Metropolitan College of Industrial Technology（东京都立产业技术高等专门学校）；Tokyo Metropolitan University（东京都立大学）
We propose a novel JPEG XT image compression with hue compensation for two-layer HDR coding. LDR images produced from JPEG XT bitstreams have some distortion in hue due to tone mapping operations. In order to suppress the color distortion, we apply a novel hue compensation method based on the maximally saturated colors. Moreover, the bitstreams generated by using the proposed method are fully compatible with the JPEG XT standard. In an experiment, the proposed method is demonstrated not only to produce images with small hue degradation but also to maintain well-mapped luminance, in terms of th…
HiMo: High-Speed Objects Motion Compensation in Point Clouds
Division of Robotics, Perception, and Learning, KTH Royal Institute of Technology（机器人、感知与学习系，皇家理工学院）；Scania Group（斯堪尼亚集团）；Autonomous Transport Solutions Lab, Scania Group（自主运输解决方案实验室，斯堪尼亚集团）
This paper proposes a novel luminance adjustment method based on automatic exposure compensation for multi-exposure image fusion. Multi-exposure image fusion is a method to produce images without saturation regions, by using photos with different exposures. In conventional works, it has been pointed out that the quality of those multi-exposure images can be improved by adjusting the luminance of them. However, how to determine the degree of adjustment has never been discussed. This paper therefore proposes a way to automatically determines the degree on the basis of the luminance distribution …
DPEC: Dual-Path Error Compensation Method for Enhanced Low-Light Image Clarity
College of Electronic Information, Sichuan University（四川大学电子信息学院）；Graduate School of Interdisciplinary Information Studies, The University of Tokyo（东京大学跨学科信息学研究院）
University of California, Berkeley（加州大学伯克利分校）；Ford Motor Co.（福特汽车公司）；ANSYS Livermore Software Technology (ANSYS-LST)（ANSYS利弗莫尔软件技术公司（ANSYS-LST））
In this paper, we introduce a probabilistic statistics solution or artificial intelligence (AI) approach to identify and quantify permanent (non-zero strain) continuum/material deformation only based on the scanned material data in the spatial configuration and the shape of the initial design configuration or the material configuration. The challenge of this problem is that we only know the scanned material data in the spatial configuration and the shape of the design configuration of three-dimensional (3D) printed products, whereas for a specific scanned material point we do not know its corr…
Technische Universität Darmstadt（达姆施塔特工业大学）；Indian Institute of Technology (IIT-BHU), Varanasi（瓦拉纳西印度理工学院（IIT-BHU））
Purpose: Electromagnetic Tracking (EMT) can partially replace X-ray guidance in minimally invasive procedures, reducing radiation in the OR. However, in this hybrid setting, EMT is disturbed by metallic distortion caused by the X-ray device. We plan to make hybrid navigation clinical reality to reduce radiation exposure for patients and surgeons, by compensating EMT error. Methods: Our online compensation strategy exploits cycle-consistent generative adversarial neural networks (CycleGAN). 3D positions are translated from various bedside environments to their bench equivalents. Domain-translat…
Friedrich-Alexander University Erlangen-Nürnberg (FAU)（埃尔朗根-纽伦堡弗里德里希-亚历山大大学）
Although fisheye cameras are in high demand in many application areas due to their large field of view, many image and video signal processing tasks such as motion compensation suffer from the introduced strong radial distortions. A recently proposed projection-based approach takes the fisheye projection into account to improve fisheye motion compensation. However, the approach does not consider the large field of view of fisheye lenses that requires the consideration of different motion planes in 3D space. We propose a novel viewport-adaptive motion compensation technique that applies the mot…
University of Chinese Academy of Sciences（中国科学院大学）；Tsinghua University（清华大学）；Hong Kong University of Science and Technology（香港科技大学）；Hokkaido University（北海道大学）
University of Minnesota（明尼苏达大学）；ENS Cachan（卡尚高等师范学校）；École des Ponts ParisTech（巴黎高科桥路学院）
This paper addresses the high precision measurement of the distortion of a digital camera from photographs. Traditionally, this distortion is measured from photographs of a flat pattern which contains aligned elements. Nevertheless, it is nearly impossible to fabricate a very flat pattern and to validate its flatness. This fact limits the attainable measurable precisions. In contrast, it is much easier to obtain physically very precise straight lines by tightly stretching good quality strings on a frame. Taking literally "plumb-line methods", we built a "calibration harp" instead of the classi…
Surveillance videos often suffer from blur and exposure distortions that occur during acquisition and storage, which can adversely influence following automatic image analysis results on video-analytic tasks. The purpose of this paper is to deploy an algorithm that can automatically assess the presence of exposure distortion in videos. In this work we to design and build one architecture for deep learning applied to recognition of distortions in a video. The goal is to know if the video present exposure distortions. Such an algorithm could be used to enhance or restoration image or to create a…
Artificial Microsaccade Compensation: Stable Vision for an Ornithopter
Department of Computer Science, University of Maryland, College Park（计算机科学系，马里兰大学，学院公园）；Faculty of Aerospace Engineering, Delft University of Technology（航空航天工程系，代尔夫特理工大学）；Institute for Advanced Computer Studies, University of Maryland, College Park（高级计算机研究 institute，马里兰大学，学院公园）
AutoIQ: An Ensemble Framework for Automatic Assessment of Geometric Distortion in Prostate Diffusion-Weighted Imaging
Biomedical Imaging Research Institute, Cedars-Sinai Medical Center（生物医学成像研究 institute， Cedars-Sinai 医疗中心）；Department of Bioengineering, University of California（生物工程系，加州大学）；Siemens Medical Solutions USA Inc.（西门子医疗解决方案美国公司）；Siemens Healthineers AG（西门子健康影像股份有限公司）；Department of Imaging, Cedars-Sinai Medical Center（成像部，Cedars-Sinai 医疗中心）；Department of Nuclear Medicine, Cedars-Sinai Medical Center（核医学部，Cedars-Sinai 医疗中心）；Department of Urology, Cedars-Sinai Medical Center（泌尿科，Cedars-Sinai 医疗中心）
Graduate School of Sciences and Engineering（科学与工程研究生院）
Motion compensation is one of the most essential methods for any video compression algorithm. Video frame prediction is a task analogous to motion compensation. In recent years, the task of frame prediction is undertaken by deep neural networks (DNNs). In this thesis we create a DNN to perform learned frame prediction and additionally implement a codec that contains our DNN. We train our network using two methods for two different goals. Firstly we train our network based on mean square error (MSE) only, aiming to obtain highest PSNR values at frame prediction and video compression. Secondly w…
Robust Phase-Shifting Profilometry for Arbitrary Motion
School of Information and Communication Engineering, University of Electronic Science and Technology of China（电子科技大学信息与通信工程学院）；College of Electrical Engineering, Sichuan University（四川大学电气工程学院）
本文提出了一种鲁棒的任意运动相位移 profilometry 方法，能够有效补偿复杂运动场景中的运动误差，提升 3D 重建精度。
Nanyang Technological University（南洋理工大学）；City University of Hong Kong（香港城市大学）；Singapore Technologies Dynamics Pte Ltd（新加坡科技动力私人有限公司）
Outdoor vision-based systems suffer from atmospheric turbulences, and rain is one of the worst factors for vision degradation. Current rain removal methods show limitations either for complex dynamic scenes, or under torrential rain with opaque occlusions. We propose a novel derain framework which applies superpixel (SP) segmentation to decompose the scene into depth consistent units. Alignment of scene contents are done at the SP level, which proves to be robust against rain occlusion interferences and fast camera motion. Two alignment output tensors, i.e., optimal temporal match tensor and s…
Head movement during scanning impedes activation detection in fMRI studies. Head motion in fMRI acquired using slice-based Echo Planar Imaging (EPI) can be estimated and compensated by aligning the images onto a reference volume through image registration. However, registering EPI images volume to volume fails to consider head motion between slices, which may lead to severely biased head motion estimates. Slice-to-volume registration can be used to estimate motion parameters for each slice by more accurately representing the image acquisition sequence. However, accurate slice to volume mapping…
Yangzhou University（扬州大学）；Institut Supérieur d'Électronique de Paris（巴黎高等电子学院）；Sorbonne University（索邦大学）；Polytechnique Montreal（蒙特利尔理工学院）；Westlake University（西湖大学）
Closed-loop architecture is widely utilized in automatic control systems and attain distinguished performance. However, classical compressive sensing systems employ open-loop architecture with separated sampling and reconstruction units. Therefore, a method of iterative compensation recovery for image compressive sensing (ICRICS) is proposed by introducing closed-loop framework into traditional compresses sensing systems. The proposed method depends on any existing approaches and upgrades their reconstruction performance by adding negative feedback structure. Theory analysis on negative feedba…
The Hong Kong University of Science and Technology（香港科技大学）；City University of Hong Kong（香港城市大学）
We propose the first general framework to automatically correct different types of geometric distortion in a single input image. Our proposed method employs convolutional neural networks (CNNs) trained by using a large synthetic distortion dataset to predict the displacement field between distorted images and corrected images. A model fitting method uses the CNN output to estimate the distortion parameters, achieving a more accurate prediction. The final corrected image is generated based on the predicted flow using an efficient, high-quality resampling method. Experimental results demonstrate…
Brown University（布朗大学）；Mitsubishi Electric Research Labs (MERL)（三菱电机研究实验室（MERL））
Range images captured by Time-of-Flight (ToF) cameras are corrupted with multipath distortions due to interaction between modulated light signals and scenes. The interaction is often complicated, which makes a model-based solution elusive. We propose a learning-based approach for removing the multipath distortions for a ToF camera in a robotic arm setup. Our approach is based on deep learning. We use the robotic arm to automatically collect a large amount of ToF range images containing various multipath distortions. The training images are automatically labeled by leveraging a high precision s…
Deep learning based Non-Rigid Volume-to-Surface Registration for Brain Shift compensation Using Point Cloud
Austrian Center for Medical Innovation and Technology（奥地利医学创新与技术中心）；Medical University of Vienna（维也纳医学大学）；University of Cambridge（剑桥大学）；Danube Private University (DPU)（多瑙私人大学（DPU））
The Hamlyn Centre for Robotic Surgery, Imperial College London（帝国理工学院哈姆林机器人外科中心）；Department of Computing, Imperial College London（帝国理工学院计算机系）；Cardiovascular Biomedical Research Unit, Royal Brompton Hospital（皇家布朗普顿医院心血管生物医学研究中心）
Purpose: Advancements in MRI Tissue Phase Velocity Mapping (TPM) allow for the acquisition of higher quality velocity cardiac images providing better assessment of regional myocardial deformation for accurate disease diagnosis, pre-operative planning and post-operative patient surveillance. Translation of TPM velocities from the scanner's reference coordinate system to the regional cardiac coordinate system requires decoupling of translational motion and motion due to myocardial deformation. Despite existing techniques for respiratory motion compensation in TPM, there is still a remaining tran…
