Image Mosaicing and Producing a Panoramic Visibility

Aim of this research paper is to take multiple input images , the input images are having some of the overlapped region with one another. Since digital cameras cant take photos of a wider view, for a wider view we need a highly sophisticated camera. It is therefore being attempted to develop enabling methodology which can convert the corresponding images captured form such cameras into a panoramic view. In this paper a n algorithm is used and applied some of the advanced function available in matlab to make this work much more efficient

Seamless, Static Multi-Texturing of 3D Meshes

In the context of 3D reconstruction, we present a static multi-texturing system yielding a seamless texture atlas calculated by combining the colour information from several photos from the same subject covering most of its surface. These pictures can be provided by shooting just one camera several times when reconstructing a static object, or a set of synchronized cameras, when dealing with a human or any other moving object. We suppress the colour seams due to image misalignments and irregular lighting conditions that multi-texturing approaches typically suffer from, while minimizing the blurring effect introduced by colour blending techniques. Our system is robust enough to compensate for the almost inevitable inaccuracies of 3D meshes obtained with visual hull–based techniques: errors in silhouette segmentation, inherently bad handling of concavities, etc

Computer Vision and Image Understanding xxx

Abstract 12 A compact visual representation, called the 3D layered, adaptive-resolution, and multi-13 perspective panorama (LAMP), is proposed for representing large-scale 3D scenes with large 14 variations of depths and obvious occlusions. Two kinds of 3D LAMP representations are 15 proposed: the relief-like LAMP and the image-based LAMP. Both types of LAMPs con-16 cisely represent almost all the information from a long image sequence. Methods to con-17 struct LAMP representations from video sequences with dominant translation are 18 provided. The relief-like LAMP is basically a single extended multi-perspective panoramic 19 view image. Each pixel has a pair of texture and depth values, but each pixel may also have 20 multiple pairs of texture-depth values to represent occlusion in layers, in addition to adap-21 tive resolution changing with depth. The image-based LAMP, on the other hand, consists of 22 a set of multi-perspective layers, each of which has a pair of 2D texture and depth maps, 23 but with adaptive time-sampling scales depending on depths of scene points. Several exam-24 ples of 3D LAMP construction for real image sequences are given. The 3D LAMP is a con-25 cise and powerful representation for image-based rendering. 2

Design of Immersive Online Hotel Walkthrough System Using Image-Based (Concentric Mosaics) Rendering

Conventional hotel booking websites only represents their services in 2D photos to show their facilities. 2D photos are just static photos that cannot be move and rotate. Imagebased virtual walkthrough for the hospitality industry is a potential technology to attract more customers. In this project, a research will be carried out to create an Image-based rendering (IBR) virtual walkthrough and panoramic-based walkthrough by using only Macromedia Flash Professional 8, Photovista Panorama 3.0 and Reality Studio for the interaction of the images. The web-based of the image-based are using the Macromedia Dreamweaver Professional 8. The images will be displayed in Adobe Flash Player 8 or higher. In making image-based walkthrough, a concentric mosaic technique is used while image mosaicing technique is applied in panoramic-based walkthrough. A comparison of the both walkthrough is compared. The study is also focus on the comparison between number of pictures and smoothness of the walkthrough. There are advantages of using different techniques such as image-based walkthrough is a real time walkthrough since the user can walk around right, left, forward and backward whereas the panoramic-based cannot experience real time walkthrough because the user can only view 360 degrees from a fixed spot

An in Depth Review Paper on Numerous Image Mosaicing Approaches and Techniques

Image mosaicing is one of the most important subjects of research in computer vision at current. Image mocaicing requires the integration of direct techniques and feature based techniques. Direct techniques are found to be very useful for mosaicing large overlapping regions, small translations and rotations while feature based techniques are useful for small overlapping regions. Feature based image mosaicing is a combination of corner detection, corner matching, motion parameters estimation and image stitching.Furthermore, image mosaicing is considered the process of obtaining a wider field-of-view of a scene from a sequence of partial views, which has been an attractive research area because of its wide range of applications, including motion detection, resolution enhancement, monitoring global land usage, and medical imaging. Numerous algorithms for image mosaicing have been proposed over the last two decades.In this paper the authors present a review on different approaches for image mosaicing and the literature over the past few years in the field of image masaicing methodologies. The authors take an overview on the various methods for image mosaicing.This review paper also provides an in depth survey of the existing image mosaicing algorithms by classifying them into several groups. For each group, the fundamental concepts are first clearly explained. Finally this paper also reviews and discusses the strength and weaknesses of all the mosaicing groups

Enhanced video indirect ophthalmoscopy (VIO) via robust mosaicing

Indirect ophthalmoscopy (IO) is the standard of care for evaluation of the neonatal retina. When recorded on video from a head-mounted camera, IO images have low quality and narrow Field of View (FOV). We present an image fusion methodology for converting a video IO recording into a single, high quality, wide-FOV mosaic that seamlessly blends the best frames in the video. To this end, we have developed fast and robust algorithms for automatic evaluation of video quality, artifact detection and removal, vessel mapping, registration, and multi-frame image fusion. Our experiments show the effectiveness of the proposed methods

Processing Camera-captured Document Images: Geometric Rectification, Mosaicing, and Layout Structure Recognition

This dissertation explores three topics: 1) geometric rectification of cameracaptured document images, 2) camera-captured document mosaicing, and 3) layout structure recognition. The first two topics pertain to camera-based document image analysis, a new trend within the OCR community. Compared to typical scanners,cameras offer convenient, flexible, portable, and non-contact image capture, which enables many new applications and breathes new life into existing ones. The third topic is related to the need for efficient metadata extraction methods, critical for managing digitized documents. The kernel of our geometric rectification framework is a novel method for estimating document shape from a single camera-captured image. Our method uses texture flows detected in printed text areas and is insensitive to occlusion. Classification of planar versus curved documents is done automatically. For planar pages, we obtain full metric rectification. For curved pages, we estimate a planar-strip approximation based on properties of developable surfaces. Our method can process any planar or smoothly curved document captured from an arbitrary position without requiring 3D data, metric data, or camera calibration. For the second topic, we design a novel registration method for document images, which produces good results in difficult situations including large displacements, severe projective distortion, small overlapping areas, and lack of distinguishable feature points. We implement a selective image composition method that outperforms conventional image blending methods in overlapping areas. It eliminates double images caused by mis-registration and preserves the sharpness in overlapping areas. We solve the third topic with a graph-based model matching framework. Layout structures are modeled by graphs, which integrate local and global features and are extensible to new features in the future. Our model can handle large variation within a class and subtle differences between classes. Through graph matching, the layout structure of a document is discovered. Our layout structure recognition technique accomplishes document classification and logical component labeling at the same time. Our model learning method enables a model to adapt to changes in classes over time