3D panoramic imaging for virtual environment construction

The project is concerned with the development of algorithms for the creation of photo-realistic 3D virtual environments, overcoming problems in mosaicing, colour and lighting changes, correspondence search speed and correspondence errors due to lack of surface texture. A number of related new algorithms have been investigated for image stitching, content based colour correction and efficient 3D surface reconstruction. All of the investigations were undertaken by using multiple views from normal digital cameras, web cameras and a ”one-shot” panoramic system. In the process of 3D reconstruction a new interest points based mosaicing method, a new interest points based colour correction method, a new hybrid feature and area based correspondence constraint and a new structured light based 3D reconstruction method have been investigated. The major contributions and results can be summarised as follows: • A new interest point based image stitching method has been proposed and investigated. The robustness of interest points has been tested and evaluated. Interest points have been proved robust to changes in lighting, viewpoint, rotation and scale. • A new interest point based method for colour correction has been proposed and investigated. The results of linear and linear plus affine colour transforms have proved more accurate than traditional diagonal transforms in accurately matching colours in panoramic images. • A new structured light based method for correspondence point based 3D reconstruction has been proposed and investigated. The method has been proved to increase the accuracy of the correspondence search for areas with low texture. Correspondence speed has also been increased with a new hybrid feature and area based correspondence search constraint. • Based on the investigation, a software framework has been developed for image based 3D virtual environment construction. The GUI includes abilities for importing images, colour correction, mosaicing, 3D surface reconstruction, texture recovery and visualisation. • 11 research papers have been published.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Mapping colour in image stitching applications

Digitally, panoramic pictures can be assembled from several individual, overlapping photographs. While the geometric alignment of these photographs has retained a lot of attention from the computer vision community, the mapping of colour, i.e. the correction of colour mismatches, has not been studied extensively. In this article, we analyze the colour rendering of today’s digital photographic systems, and propose a method to correct for colour differences. The colour correction consists in retrieving linearized relative scene referred data from uncalibrated images by estimating the Opto-Electronic Conversion Function (OECF) and correcting for exposure, white-point, and vignetting variations between the individual pictures. Different OECF estimation methods are presented and evaluated in conjunction with motion estimation. The resulting panoramas, shown on examples using slides and digital photographs, yield much-improved visual quality compared to stitching using only motion estimation. Additionally, we show that colour correction can also improve the geometrical alignment

Damage detection and monitoring for tunnel inspection based on computer vision

The deterioration of the underground infrastructure of the major cities around the world, due to ageing, has become a topic of great concern among engineers. Visual inspection, as part of the routine maintenance procedures, is a common practice used in the condition assessment of infrastructure to ensure its safety and serviceability. This practice, however, is labour-intensive, costly and inaccurate and, therefore, a new system based on computer vision technology is presented in this thesis, aiming to tackle these inadequacies. This thesis proposes a novel mosaicing system for inspection reporting, which can create an almost distortion-free mosaic of tunnels, thus allowing a large area of tunnels to be visualised. The system relies on Structure from Motion (SFM), which enables the system to cope with images with a general camera motion, in contrast to standard mosaicing software that can cope only with a strict camera motion. The system involves the automatic robust estimation of a 3D cylindrical surface using a Support Vector Machine to classify 3D points to improve the accuracy of the estimation. It is shown that some curvatures are observed in the mosaics when an inaccurate surface is used for mosaicing, while the mosaics from a surface estimated using the proposed method are almost distortion-free. New feature matching algorithms aiming to improve the performance of SFM systems are proposed. These algorithms apply a spatial consistency constraint to match features with a similar topography, in contrast to other matching algorithms that rely on matching based on the similar appearance of local image patches. The Shape Context and Random Forest algorithms are combined in the proposed algorithm, revealing promising results. The final contribution is a new change detection system for monitoring cracks in multi-temporal images. The system can cope with images with a general camera motion achieved by geometrical registration using SFM, unlike other systems that assume fixed or controlled cameras. The system performs photometric normalisation to cope with illumination variation in the images, and also a motion-invariant change detection algorithm is applied to handle deformable objects. It is shown that the results from the proposed change detection system are still impractical for use with tunnel images from a real environment, and further study is required

텍스트와 특징점 기반의 목적함수 최적화를 이용한 문서와 텍스트 평활화 기법

학위논문 (박사)-- 서울대학교 대학원 : 전기·컴퓨터공학부, 2014. 8. 조남익.There are many techniques and applications that detect and recognize text information in the images, e.g., document retrieval using the camera-captured document image, book reader for visually impaired, and augmented reality based on text recognition. In these applications, the planar surfaces which contain the text are often distorted in the captured image due to the perspective view (e.g., road signs), curvature (e.g., unfolded books), and wrinkles (e.g., old documents). Specifically, recovering the original document texture by removing these distortions from the camera-captured document images is called the document rectification. In this dissertation, new text surface rectification algorithms are proposed, for improving text recognition accuracy and visual quality. The proposed methods are categorized into 3 types depending on the types of the input. The contributions of the proposed methods can be summarized as follows. In the first rectification algorithm, the dense text-lines in the documents are employed to rectify the images. Unlike the conventional approaches, the proposed method does not directly use the text-line. Instead, the proposed method use the discrete representation of text-lines and text-blocks which are the sets of connected components. Also, the geometric distortion caused by page curl and perspective view are modeled as generalized cylindrical surfaces and camera rotation respectively. With these distortion model and discrete representation of the features, a cost function whose minimization yields parameters of the distortion model is developed. In the cost function, the properties of the pages such as text-block alignment, line-spacing, and the straightness of text-lines are encoded. By describing the text features using the sets of discrete points, the cost function can be easily defined and well solved by Levenberg-Marquadt algorithm. Experiments show that the proposed method works well for the various layouts and curved surfaces, and compares favorably with the conventional methods on the standard dataset. The second algorithm is a unified framework to rectify and stitch multiple document images using visual feature points instead of text lines. This is similar to the method employed in general image stitching algorithm. However, the general image stitching algorithm usually assumes fixed center of camera, which is not taken for granted in capturing the document. To deal with the camera motion between images, a new parametric family of motion model is proposed in this dissertation. Besides, to remove the ambiguity in the reference plane, a new cost function is developed to impose the constraints on the reference plane. This enables the estimation of physically correct reference plane without prior knowledge. The estimated reference plane can also be used to rectify the stitching result. Furthermore, the proposed method can be applied to any other planar object such as building facades or mural paintings as well as the camera-captured document image since it employs the general features. The third rectification method is based on scene text detection algorithm, which is independent from the language model. The conventional methods assume that a character consists of a single connected component (CC) like English alphabet. However, this assumption is brittle in the Asian characters such as Korean, Chinese, and Japanese, where a single character consists of several CCs. Therefore, it is difficult to divide CCs into text lines without language model. To alleviate this problem, the proposed method clusters the candidate regions based on the similarity measure considering inter-character relation. The adjacency measure is trained on the data set labeled with the bounding box of text region. Non-text regions that remain after clustering are filtered out in text/non-text classification step. Final text regions are merged or divided into each text line considering the orientation and location. The detected text is rectified using the orientation of text-line and vertical strokes. The proposed method outperforms state-of-the-art algorithms in English as well as Asian characters in the extensive experiments.1 Introduction 1 1.1 Document rectification via text-line based optimization . . . . . . . 2 1.2 A unified approach of rectification and stitching for document images 4 1.3 Rectification via scene text detection . . . . . . . . . . . . . . . . . . 5 1.4 Contents . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 2 Related work 9 2.1 Document rectification . . . . . . . . . . . . . . . . . . . . . . . . . . 9 2.1.1 Document dewarping without text-lines . . . . . . . . . . . . 9 2.1.2 Document dewarping with text-lines . . . . . . . . . . . . . . 10 2.1.3 Text-block identification and text-line extraction . . . . . . . 11 2.2 Document stitching . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 2.3 Scene text detection . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 3 Document rectification based on text-lines 15 3.1 Proposed approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 3.1.1 Image acquisition model . . . . . . . . . . . . . . . . . . . . . 16 3.1.2 Proposed approach to document dewarping . . . . . . . . . . 18 3.2 Proposed cost function and its optimization . . . . . . . . . . . . . . 22 3.2.1 Design of Estr(·) . . . . . . . . . . . . . . . . . . . . . . . . . 22 3.2.2 Minimization of Estr(·) . . . . . . . . . . . . . . . . . . . . . 23 3.2.3 Alignment type classification . . . . . . . . . . . . . . . . . . 28 3.2.4 Design of Ealign(·) . . . . . . . . . . . . . . . . . . . . . . . . 29 3.2.5 Design of Espacing(·) . . . . . . . . . . . . . . . . . . . . . . . 31 3.3 Extension to unfolded book surfaces . . . . . . . . . . . . . . . . . . 32 3.4 Experimental result . . . . . . . . . . . . . . . . . . . . . . . . . . . 34 3.4.1 Experiments on synthetic data . . . . . . . . . . . . . . . . . 36 3.4.2 Experiments on real images . . . . . . . . . . . . . . . . . . . 39 3.4.3 Comparison with existing methods . . . . . . . . . . . . . . . 43 3.4.4 Limitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 4 Document rectification based on feature detection 49 4.1 Proposed approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 4.2 Proposed cost function and its optimization . . . . . . . . . . . . . . 51 4.2.1 Notations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 4.2.2 Homography between the i-th image and E . . . . . . . . . 52 4.2.3 Proposed cost function . . . . . . . . . . . . . . . . . . . . . . 53 4.2.4 Optimization . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 4.2.5 Relation to the model in [17] . . . . . . . . . . . . . . . . . . 55 4.3 Post-processing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55 4.3.1 Classification of two cases . . . . . . . . . . . . . . . . . . . . 56 4.3.2 Skew removal . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 4.4 Experimental results . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 4.4.1 Quantitative evaluation on metric reconstruction performance 57 4.4.2 Experiments on real images . . . . . . . . . . . . . . . . . . . 58 5 Scene text detection and rectification 67 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.1.1 Contribution . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 5.1.2 Proposed approach . . . . . . . . . . . . . . . . . . . . . . . . 69 5.2 Candidate region detection . . . . . . . . . . . . . . . . . . . . . . . 70 5.2.1 CC extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 5.2.2 Computation of similarity between CCs . . . . . . . . . . . . 70 5.2.3 CC clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.3 Rectification of candidate region . . . . . . . . . . . . . . . . . . . . 73 5.4 Text/non-text classification . . . . . . . . . . . . . . . . . . . . . . . 76 5.5 Experimental result . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 5.5.1 Experimental results on ICDAR 2011 dataset . . . . . . . . . 80 5.5.2 Experimental results on the Asian character dataset . . . . . 80 6 Conclusion 83 Bibliography 87 Abstract (Korean) 97Docto

Omnidirectional Stereo Vision for Autonomous Vehicles

Environment perception with cameras is an important requirement for many applications for autonomous vehicles and robots. This work presents a stereoscopic omnidirectional camera system for autonomous vehicles which resolves the problem of a limited field of view and provides a 360° panoramic view of the environment. We present a new projection model for these cameras and show that the camera setup overcomes major drawbacks of traditional perspective cameras in many applications

Automatic Analysis of Lens Distortions in Image Registration

Geometric image registration by estimating homographies is an important processing step in a wide variety of computer vision applications. The 2D registration of two images does not require an explicit reconstruction of intrinsic or extrinsic camera parameters. However, correcting images for non-linear lens distortions is highly recommended. Unfortunately, standard calibration techniques are sometimes difficult to apply and reliable estimations of lens distortions can only rarely be obtained. In this paper we present a new technique for automatically detecting and categorising lens distortions in pairs of images by analysing registration results. The approach is based on a new metric for registration quality assessment and facilitates a PCA-based statistical model for classifying distortion effects. In doing so the overall importance for lens calibration and image corrections can be checked, and a measure for the efficiency of accordant correction steps is given

Modeling and Simulation in Engineering

This book provides an open platform to establish and share knowledge developed by scholars, scientists, and engineers from all over the world, about various applications of the modeling and simulation in the design process of products, in various engineering fields. The book consists of 12 chapters arranged in two sections (3D Modeling and Virtual Prototyping), reflecting the multidimensionality of applications related to modeling and simulation. Some of the most recent modeling and simulation techniques, as well as some of the most accurate and sophisticated software in treating complex systems, are applied. All the original contributions in this book are jointed by the basic principle of a successful modeling and simulation process: as complex as necessary, and as simple as possible. The idea is to manipulate the simplifying assumptions in a way that reduces the complexity of the model (in order to make a real-time simulation), but without altering the precision of the results

Efficient Distance Accuracy Estimation Of Real-World Environments In Virtual Reality Head-Mounted Displays

Virtual reality (VR) is a very promising technology with many compelling industrial applications. As many advancements have been made recently to deploy and use VR technology in virtual environments, they are still less mature to be used to render real environments. The current VR systems settings, which are developed for virtual environments rendering, fail to adequately address the challenges of capturing and displaying real-world virtual reality that these systems entail. Before these systems can be used in real life settings, their performance needs to be investigated, more specifically, depth perception and how distances to objects in the rendered scenes are estimated. The perceived depth is influenced by Head Mounted Displays (HMD) that inevitability decrease the virtual content’s depth perception. Distances are consistently underestimated in virtual environments (VEs) compared to the real world. The reason behind this underestimation is still not understood. This thesis investigates another version of this kind of system, that to the best of authors knowledge has not been explored by any previous research. Previous research used a computer-generated scene. This work is examining distance estimation in real environments rendered to Head-Mounted Displays, where distance estimations is among the most challenging issues that are still investigated and not fully understood.This thesis introduces a dual-camera video feed system through a virtual reality head mounted display with two models: a video-based and a static photo-based model, in which, the purpose is to explore whether the misjudgment of distances in HMDs could be due to a lack of realism, or not, with the use of a real-world scene rendering system. Distance judgments performance in the real world and these two evaluated VE models were compared using protocols already proven to accurately measure real-world distance estimations. An improved model based on enhancing the field of view (FOV) of the displayed scenes to improve distance judgements when displaying real-world VR content to HMDs was developed; allowing to mitigate the limited FOV, which is among the first potential causes of distance underestimation, specially, the mismatch of FOV between the camera and the HMD field of views. The proposed model is using a set of two cameras to generate the video instead of hundreds of input cameras or tens of cameras mounted on a circular rig as previous works from the literature. First Results from the first implementation of this system found that when the model was rendered as static photo-based, the underestimation was less as compared with the live video feed rendering. The video-based (real + HMD) model and the static photo-based (real + photo + HMD) model averaged 80.2% of the actual distance, and 81.4% respectively compared to the Real-World estimations that averaged 92.4%. The improved developed approach (Real + HMD + FOV) was compared to these two models and showed an improvement of 11%, increasing the estimation accuracy from 80% to 91% and reducing the estimation error from 1.29% to 0.56%. This thesis results present strong evidence of the need for novel distance estimation improvements methods for real world VR content systems and provides effective initial work towards this goal

Applying image processing techniques to pose estimation and view synthesis.

Fung Yiu-fai Phineas.Thesis (M.Phil.)--Chinese University of Hong Kong, 1999.Includes bibliographical references (leaves 142-148).Abstracts in English and Chinese.Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Model-based Pose Estimation --- p.3Chapter 1.1.1 --- Application - 3D Motion Tracking --- p.4Chapter 1.2 --- Image-based View Synthesis --- p.4Chapter 1.3 --- Thesis Contribution --- p.7Chapter 1.4 --- Thesis Outline --- p.8Chapter 2 --- General Background --- p.9Chapter 2.1 --- Notations --- p.9Chapter 2.2 --- Camera Models --- p.10Chapter 2.2.1 --- Generic Camera Model --- p.10Chapter 2.2.2 --- Full-perspective Camera Model --- p.11Chapter 2.2.3 --- Affine Camera Model --- p.12Chapter 2.2.4 --- Weak-perspective Camera Model --- p.13Chapter 2.2.5 --- Paraperspective Camera Model --- p.14Chapter 2.3 --- Model-based Motion Analysis --- p.15Chapter 2.3.1 --- Point Correspondences --- p.16Chapter 2.3.2 --- Line Correspondences --- p.18Chapter 2.3.3 --- Angle Correspondences --- p.19Chapter 2.4 --- Panoramic Representation --- p.20Chapter 2.4.1 --- Static Mosaic --- p.21Chapter 2.4.2 --- Dynamic Mosaic --- p.22Chapter 2.4.3 --- Temporal Pyramid --- p.23Chapter 2.4.4 --- Spatial Pyramid --- p.23Chapter 2.5 --- Image Pre-processing --- p.24Chapter 2.5.1 --- Feature Extraction --- p.24Chapter 2.5.2 --- Spatial Filtering --- p.27Chapter 2.5.3 --- Local Enhancement --- p.31Chapter 2.5.4 --- Dynamic Range Stretching or Compression --- p.32Chapter 2.5.5 --- YIQ Color Model --- p.33Chapter 3 --- Model-based Pose Estimation --- p.35Chapter 3.1 --- Previous Work --- p.35Chapter 3.1.1 --- Estimation from Established Correspondences --- p.36Chapter 3.1.2 --- Direct Estimation from Image Intensities --- p.49Chapter 3.1.3 --- Perspective-3-Point Problem --- p.51Chapter 3.2 --- Our Iterative P3P Algorithm --- p.58Chapter 3.2.1 --- Gauss-Newton Method --- p.60Chapter 3.2.2 --- Dealing with Ambiguity --- p.61Chapter 3.2.3 --- 3D-to-3D Motion Estimation --- p.66Chapter 3.3 --- Experimental Results --- p.68Chapter 3.3.1 --- Synthetic Data --- p.68Chapter 3.3.2 --- Real Images --- p.72Chapter 3.4 --- Discussions --- p.73Chapter 4 --- Panoramic View Analysis --- p.76Chapter 4.1 --- Advanced Mosaic Representation --- p.76Chapter 4.1.1 --- Frame Alignment Policy --- p.77Chapter 4.1.2 --- Multi-resolution Representation --- p.77Chapter 4.1.3 --- Parallax-based Representation --- p.78Chapter 4.1.4 --- Multiple Moving Objects --- p.79Chapter 4.1.5 --- Layers and Tiles --- p.79Chapter 4.2 --- Panorama Construction --- p.79Chapter 4.2.1 --- Image Acquisition --- p.80Chapter 4.2.2 --- Image Alignment --- p.82Chapter 4.2.3 --- Image Integration --- p.88Chapter 4.2.4 --- Significant Residual Estimation --- p.89Chapter 4.3 --- Advanced Alignment Algorithms --- p.90Chapter 4.3.1 --- Patch-based Alignment --- p.91Chapter 4.3.2 --- Global Alignment (Block Adjustment) --- p.92Chapter 4.3.3 --- Local Alignment (Deghosting) --- p.93Chapter 4.4 --- Mosaic Application --- p.94Chapter 4.4.1 --- Visualization Tool --- p.94Chapter 4.4.2 --- Video Manipulation --- p.95Chapter 4.5 --- Experimental Results --- p.96Chapter 5 --- Panoramic Walkthrough --- p.99Chapter 5.1 --- Problem Statement and Notations --- p.100Chapter 5.2 --- Previous Work --- p.101Chapter 5.2.1 --- 3D Modeling and Rendering --- p.102Chapter 5.2.2 --- Branching Movies --- p.103Chapter 5.2.3 --- Texture Window Scaling --- p.104Chapter 5.2.4 --- Problems with Simple Texture Window Scaling --- p.105Chapter 5.3 --- Our Walkthrough Approach --- p.106Chapter 5.3.1 --- Cylindrical Projection onto Image Plane --- p.106Chapter 5.3.2 --- Generating Intermediate Frames --- p.108Chapter 5.3.3 --- Occlusion Handling --- p.114Chapter 5.4 --- Experimental Results --- p.116Chapter 5.5 --- Discussions --- p.116Chapter 6 --- Conclusion --- p.121Chapter A --- Formulation of Fischler and Bolles' Method for P3P Problems --- p.123Chapter B --- Derivation of z1 and z3 in terms of z2 --- p.127Chapter C --- Derivation of e1 and e2 --- p.129Chapter D --- Derivation of the Update Rule for Gauss-Newton Method --- p.130Chapter E --- Proof of (λ1λ2-λ 4）>〉0 --- p.132Chapter F --- Derivation of φ and hi --- p.133Chapter G --- Derivation of w1j to w4j --- p.134Chapter H --- More Experimental Results on Panoramic Stitching Algorithms --- p.138Bibliography --- p.14

Omnidirectional Stereo Vision for Autonomous Vehicles

Environment perception with cameras is an important requirement for many applications for autonomous vehicles and robots. This work presents a stereoscopic omnidirectional camera system for autonomous vehicles which resolves the problem of a limited field of view and provides a 360° panoramic view of the environment. We present a new projection model for these cameras and show that the camera setup overcomes major drawbacks of traditional perspective cameras in many applications