Panoramic Human Structure Maintenance based on Invariant Features of Video Frames

[[abstract]]Panoramic photography is becoming a very popular and commonly available feature in the mobile handheld devices nowadays. In traditional panoramic photography, the human structure often becomes messy if the human changes position in the scene or during the combination step of the human structure and natural background. In this paper, we present an effective method in panorama creation to maintain the main structure of human in the panorama. In the proposed method, we use an automatic method of feature matching, and the energy map of seam carving is used to avoid the overlapping of human with the natural background. The contributions of this proposal include automated panoramic creation method and it solves the human ghost generation problem in panorama by maintaining the structure of human by energy map. Experimental results prove that the proposed system can be effectively used to compose panoramic photographs and maintain human structure in panorama.[[incitationindex]]SCI[[booktype]]電子

Remote Visual Observation of Real Places Through Virtual Reality Headsets

Virtual Reality has always represented a fascinating yet powerful opportunity that has attracted studies and technology developments, especially since the latest release on the market of powerful high-resolution and wide field-of-view VR headsets. While the great potential of such VR systems is common and accepted knowledge, issues remain related to how to design systems and setups capable of fully exploiting the latest hardware advances. The aim of the proposed research is to study and understand how to increase the perceived level of realism and sense of presence when remotely observing real places through VR headset displays. Hence, to produce a set of guidelines that give directions to system designers about how to optimize the display-camera setup to enhance performance, focusing on remote visual observation of real places. The outcome of this investigation represents unique knowledge that is believed to be very beneficial for better VR headset designs towards improved remote observation systems. To achieve the proposed goal, this thesis presents a thorough investigation of existing literature and previous researches, which is carried out systematically to identify the most important factors ruling realism, depth perception, comfort, and sense of presence in VR headset observation. Once identified, these factors are further discussed and assessed through a series of experiments and usability studies, based on a predefined set of research questions. More specifically, the role of familiarity with the observed place, the role of the environment characteristics shown to the viewer, and the role of the display used for the remote observation of the virtual environment are further investigated. To gain more insights, two usability studies are proposed with the aim of defining guidelines and best practices. The main outcomes from the two studies demonstrate that test users can experience an enhanced realistic observation when natural features, higher resolution displays, natural illumination, and high image contrast are used in Mobile VR. In terms of comfort, simple scene layouts and relaxing environments are considered ideal to reduce visual fatigue and eye strain. Furthermore, sense of presence increases when observed environments induce strong emotions, and depth perception improves in VR when several monocular cues such as lights and shadows are combined with binocular depth cues. Based on these results, this investigation then presents a focused evaluation on the outcomes and introduces an innovative eye-adapted High Dynamic Range (HDR) approach, which the author believes to be of great improvement in the context of remote observation when combined with eye-tracked VR headsets. Within this purpose, a third user study is proposed to compare static HDR and eye-adapted HDR observation in VR, to assess that the latter can improve realism, depth perception, sense of presence, and in certain cases even comfort. Results from this last study confirmed the author expectations, proving that eye-adapted HDR and eye tracking should be used to achieve best visual performances for remote observation in modern VR systems

Panoramic Multimedia Walkthrough ofUTP Campus

This report is on the project that aims to apply the concept of Virtual Walkthrough using Panoramic Images to promote the facilities available in the campus of University of Technology PETRONAS (UTP). A panorama can be defined as a wide picture or image that shows 100° to 360° widths. The end result of the project will be a Web application that provides imaging information about the hotspots in UTP. The system is meant to promote UTP to potential students who want to enroll themselves into the university; the majority is students who have just left secondary school. This project is aimed to contribute towards multidimensional disciplines such as virtual reality technology and multimedia

Progressive Refinement Imaging

This paper presents a novel technique for progressive online integration of uncalibrated image sequences with substantial geometric and/or photometric discrepancies into a single, geometrically and photometrically consistent image. Our approach can handle large sets of images, acquired from a nearly planar or infinitely distant scene at different resolutions in object domain and under variable local or global illumination conditions. It allows for efficient user guidance as its progressive nature provides a valid and consistent reconstruction at any moment during the online refinement process. // Our approach avoids global optimization techniques, as commonly used in the field of image refinement, and progressively incorporates new imagery into a dynamically extendable and memory‐efficient Laplacian pyramid. Our image registration process includes a coarse homography and a local refinement stage using optical flow. Photometric consistency is achieved by retaining the photometric intensities given in a reference image, while it is being refined. Globally blurred imagery and local geometric inconsistencies due to, e.g. motion are detected and removed prior to image fusion. // We demonstrate the quality and robustness of our approach using several image and video sequences, including handheld acquisition with mobile phones and zooming sequences with consumer cameras

Doctor of Philosophy

dissertationInteractive editing and manipulation of digital media is a fundamental component in digital content creation. One media in particular, digital imagery, has seen a recent increase in popularity of its large or even massive image formats. Unfortunately, current systems and techniques are rarely concerned with scalability or usability with these large images. Moreover, processing massive (or even large) imagery is assumed to be an off-line, automatic process, although many problems associated with these datasets require human intervention for high quality results. This dissertation details how to design interactive image techniques that scale. In particular, massive imagery is typically constructed as a seamless mosaic of many smaller images. The focus of this work is the creation of new technologies to enable user interaction in the formation of these large mosaics. While an interactive system for all stages of the mosaic creation pipeline is a long-term research goal, this dissertation concentrates on the last phase of the mosaic creation pipeline - the composition of registered images into a seamless composite. The work detailed in this dissertation provides the technologies to fully realize interactive editing in mosaic composition on image collections ranging from the very small to massive in scale

Smart 360-Degree Photography for Enhancing Construction Progress Reporting

Periodical construction progress reports are essential in project evaluation and review. They impact stakeholder communication, transparency, and trust. While conventional pictures and videos (Captured Data) are currently the norm in supporting progress reporting, their use is not always efficient. As a result, 360-degree photography can now be integrated into progress reports using commercial products. However, there is a shortage of academic studies that actually assess the effectiveness of such tools. The goal of this research is to develop and test a user-friendly framework for progress reporting that integrates 360-degree photography. The research started by collecting information from construction experts to determine the used methods of progress reporting and the level of utilization of 360-degree photography in the MENA region. Then, an innovative framework that integrates 360-degree photography was developed. To evaluate the effectiveness of the developed framework, a 3-month pilot study was conducted where the developed framework was utilized in three ongoing construction projects in Egypt. After a thorough analysis of meeting, correspondence, and interview transcripts before, during, and after using the technology; the results indicate that the proper use of 360-degree photography in progress reports has a positive impact on the overall coordination, transparency, trust, and responsibility division between the project parties. The obstacles of utilizing such framework and recommendations on how to overcome them were also discussed so that future researchers can further improve the process of progress reporting

Videos in Context for Telecommunication and Spatial Browsing

The research presented in this thesis explores the use of videos embedded in panoramic imagery to transmit spatial and temporal information describing remote environments and their dynamics. Virtual environments (VEs) through which users can explore remote locations are rapidly emerging as a popular medium of presence and remote collaboration. However, capturing visual representation of locations to be used in VEs is usually a tedious process that requires either manual modelling of environments or the employment of specific hardware. Capturing environment dynamics is not straightforward either, and it is usually performed through specific tracking hardware. Similarly, browsing large unstructured video-collections with available tools is difficult, as the abundance of spatial and temporal information makes them hard to comprehend. At the same time, on a spectrum between 3D VEs and 2D images, panoramas lie in between, as they offer the same 2D images accessibility while preserving 3D virtual environments surrounding representation. For this reason, panoramas are an attractive basis for videoconferencing and browsing tools as they can relate several videos temporally and spatially. This research explores methods to acquire, fuse, render and stream data coming from heterogeneous cameras, with the help of panoramic imagery. Three distinct but interrelated questions are addressed. First, the thesis considers how spatially localised video can be used to increase the spatial information transmitted during video mediated communication, and if this improves quality of communication. Second, the research asks whether videos in panoramic context can be used to convey spatial and temporal information of a remote place and the dynamics within, and if this improves users' performance in tasks that require spatio-temporal thinking. Finally, the thesis considers whether there is an impact of display type on reasoning about events within videos in panoramic context. These research questions were investigated over three experiments, covering scenarios common to computer-supported cooperative work and video browsing. To support the investigation, two distinct video+context systems were developed. The first telecommunication experiment compared our videos in context interface with fully-panoramic video and conventional webcam video conferencing in an object placement scenario. The second experiment investigated the impact of videos in panoramic context on quality of spatio-temporal thinking during localization tasks. To support the experiment, a novel interface to video-collection in panoramic context was developed and compared with common video-browsing tools. The final experimental study investigated the impact of display type on reasoning about events. The study explored three adaptations of our video-collection interface to three display types. The overall conclusion is that videos in panoramic context offer a valid solution to spatio-temporal exploration of remote locations. Our approach presents a richer visual representation in terms of space and time than standard tools, showing that providing panoramic contexts to video collections makes spatio-temporal tasks easier. To this end, videos in context are suitable alternative to more difficult, and often expensive solutions. These findings are beneficial to many applications, including teleconferencing, virtual tourism and remote assistance

Алгоритм формирования видеопанорамы и его программная реализация c применением технологии CUDA

Разработан и реализован с применением языка CUDA С алгоритм формирования видеопанорамы по информации от пяти различных предварительно откалиброванных камер с перекрывающимися полями зрения. Для управляемого оператором окна интереса размером 1024768 пикселей с частотой 50 кадров/с реализованы операции компенсации дисторсии, «сшивки» изображений на внутренней поверхности виртуальной сферы и сглаживания перепадов яркости (блендинга)

Viewpoint-Free Photography for Virtual Reality

Viewpoint-free photography, i.e., interactively controlling the viewpoint of a photograph after capture, is a standing challenge. In this thesis, we investigate algorithms to enable viewpoint-free photography for virtual reality (VR) from casual capture, i.e., from footage easily captured with consumer cameras. We build on an extensive body of work in image-based rendering (IBR). Given images of an object or scene, IBR methods aim to predict the appearance of an image taken from a novel perspective. Most IBR methods focus on full or near-interpolation, where the output viewpoints either lie directly between captured images, or nearby. These methods are not suitable for VR, where the user has significant range of motion and can look in all directions. Thus, it is essential to create viewpoint-free photos with a wide field-of-view and sufficient positional freedom to cover the range of motion a user might experience in VR. We focus on two VR experiences: 1) Seated VR experiences, where the user can lean in different directions. This simplifies the problem, as the scene is only observed from a small range of viewpoints. Thus, we focus on easy capture, showing how to turn panorama-style capture into 3D photos, a simple representation for viewpoint-free photos, and also how to speed up processing so users can see the final result on-site. 2) Room-scale VR experiences, where the user can explore vastly different perspectives. This is challenging: More input footage is needed, maintaining real-time display rates becomes difficult, view-dependent appearance and object backsides need to be modelled, all while preventing noticeable mistakes. We address these challenges by: (1) creating refined geometry for each input photograph, (2) using a fast tiled rendering algorithm to achieve real-time display rates, and (3) using a convolutional neural network to hide visual mistakes during compositing. Overall, we provide evidence that viewpoint-free photography is feasible from casual capture. We thoroughly compare with the state-of-the-art, showing that our methods achieve both a numerical improvement and a clear increase in visual quality for both seated and room-scale VR experiences

Multi-Projective Camera-Calibration, Modeling, and Integration in Mobile-Mapping Systems

Optical systems are vital parts of most modern systems such as mobile mapping systems, autonomous cars, unmanned aerial vehicles (UAV), and game consoles. Multi-camera systems (MCS) are commonly employed for precise mapping including aerial and close-range applications. In the first part of this thesis a simple and practical calibration model and a calibration scheme for multi-projective cameras (MPC) is presented. The calibration scheme is enabled by implementing a camera test field equipped with a customized coded target as FGI’s camera calibration room. The first hypothesis was that a test field is necessary to calibrate an MPC. Two commercially available MPCs with 6 and 36 cameras were successfully calibrated in FGI’s calibration room. The calibration results suggest that the proposed model is able to estimate parameters of the MPCs with high geometric accuracy, and reveals the internal structure of the MPCs. In the second part, the applicability of an MPC calibrated by the proposed approach was investigated in a mobile mapping system (MMS). The second hypothesis was that a system calibration is necessary to achieve high geometric accuracies in a multi-camera MMS. The MPC model was updated to consider mounting parameters with respect to GNSS and IMU. A system calibration scheme for an MMS was proposed. The results showed that the proposed system calibration approach was able to produce accurate results by direct georeferencing of multi-images in an MMS. Results of geometric assessments suggested that a centimeter-level accuracy is achievable by employing the proposed approach. A novel correspondence map is demonstrated for MPCs that helps to create metric panoramas. In the third part, the problem of real-time trajectory estimation of a UAV equipped with a projective camera was studied. The main objective of this part was to address the problem of real-time monocular simultaneous localization and mapping (SLAM) of a UAV. An angular framework was discussed to address the gimbal lock singular situation. The results suggest that the proposed solution is an effective and rigorous monocular SLAM for aerial cases where the object is near-planar. In the last part, the problem of tree-species classification by a UAV equipped with two hyper-spectral an RGB cameras was studied. The objective of this study was to investigate different aspects of a precise tree-species classification problem by employing state-of-art methods. A 3D convolutional neural-network (3D-CNN) and a multi-layered perceptron (MLP) were proposed and compared. Both classifiers were highly successful in their tasks, while the 3D-CNN was superior in performance. The classification result was the most accurate results published in comparison to other works.Optiset kuvauslaitteet ovat keskeisessä roolissa moderneissa konenäköön perustuvissa järjestelmissä kuten autonomiset autot, miehittämättömät lentolaitteet (UAV) ja pelikonsolit. Tällaisissa sovelluksissa hyödynnetään tyypillisesti monikamerajärjestelmiä. Väitöskirjan ensimmäisessä osassa kehitetään yksinkertainen ja käytännöllinen matemaattinen malli ja kalibrointimenetelmä monikamerajärjestelmille. Koodatut kohteet ovat keinotekoisia kuvia, joita voidaan tulostaa esimerkiksi A4-paperiarkeille ja jotka voidaan mitata automaattisesti tietokonealgoritmeillä. Matemaattinen malli määritetään hyödyntämällä 3-ulotteista kamerakalibrointihuonetta, johon kehitetyt koodatut kohteet asennetaan. Kaksi kaupallista monikamerajärjestelmää, jotka muodostuvat 6 ja 36 erillisestä kamerasta, kalibroitiin onnistuneesti ehdotetulla menetelmällä. Tulokset osoittivat, että menetelmä tuotti tarkat estimaatit monikamerajärjestelmän geometrisille parametreille ja että estimoidut parametrit vastasivat hyvin kameran sisäistä rakennetta. Työn toisessa osassa tutkittiin ehdotetulla menetelmällä kalibroidun monikamerajärjestelmän mittauskäyttöä liikkuvassa kartoitusjärjestelmässä (MMS). Tavoitteena oli kehittää ja tutkia korkean geometrisen tarkkuuden kartoitusmittauksia. Monikameramallia laajennettiin navigointilaitteiston paikannus ja kallistussensoreihin (GNSS/IMU) liittyvillä parametreillä ja ehdotettiin järjestelmäkalibrointimenetelmää liikkuvalle kartoitusjärjestelmälle. Kalibroidulla järjestelmällä saavutettiin senttimetritarkkuus suorapaikannusmittauksissa. Työssä myös esitettiin monikuville vastaavuuskartta, joka mahdollistaa metristen panoraamojen luonnin monikamarajärjestelmän kuvista. Kolmannessa osassa tutkittiin UAV:​​n liikeradan reaaliaikaista estimointia hyödyntäen yhteen kameraan perustuvaa menetelmää. Päätavoitteena oli kehittää monokulaariseen kuvaamiseen perustuva reaaliaikaisen samanaikaisen paikannuksen ja kartoituksen (SLAM) menetelmä. Työssä ehdotettiin moniresoluutioisiin kuvapyramideihin ja eteneviin suorakulmaisiin alueisiin perustuvaa sovitusmenetelmää. Ehdotetulla lähestymistavalla pystyttiin alentamaan yhteensovittamisen kustannuksia sovituksen tarkkuuden säilyessä muuttumattomana. Kardaanilukko (gimbal lock) tilanteen käsittelemiseksi toteutettiin uusi kulmajärjestelmä. Tulokset osoittivat, että ehdotettu ratkaisu oli tehokas ja tarkka tilanteissa joissa kohde on lähes tasomainen. Suorituskyvyn arviointi osoitti, että kehitetty menetelmä täytti UAV:n reaaliaikaiselle reitinestimoinnille annetut aika- ja tarkkuustavoitteet. Työn viimeisessä osassa tutkittiin puulajiluokitusta käyttäen hyperspektri- ja RGB-kameralla varustettua UAV-järjestelmää. Tavoitteena oli tutkia uusien koneoppimismenetelmien käyttöä tarkassa puulajiluokituksessa ja lisäksi vertailla hyperspektri ja RGB-aineistojen suorituskykyä. Työssä verrattiin 3D-konvoluutiohermoverkkoa (3D-CNN) ja monikerroksista perceptronia (MLP). Molemmat luokittelijat tuottivat hyvän luokittelutarkkuuden, mutta 3D-CNN tuotti tarkimmat tulokset. Saavutettu tarkkuus oli parempi kuin aikaisemmat julkaistut tulokset vastaavilla aineistoilla. Hyperspektrisen ja RGB-datan yhdistelmä tuotti parhaan tarkkuuden, mutta myös RGB-kamera yksin tuotti tarkan tuloksen ja on edullinen ja tehokas aineisto monille luokittelusovelluksille