Panoramic mapping on a mobile phone GPU

IEEE Transactions on Consumer Electronics, 2010

This paper addresses the problem of creating high-resolution and high-quality panoramic images from long image sequences with very different colors and luminance in source images. A fast stitching approach is proposed for combining a set of source images into a panoramic image using little memory, and implemented on mobile phones. In this approach, color correction reduces color differences of source images and balances colors and luminance in the whole image sequence, dynamic programming finds optimal seams in overlapping areas between adjacent images and merges them together, and image blending further smoothens color transitions and hides visible seams and stitching artifacts. A sequential panorama stitching procedure constructs panoramic images. The advantages include fast processing speed using dynamic programming for optimal seam finding, reducing memory needs by using the sequential panorama stitching, and improved quality of image labeling and blending due to the use of color correction. The approach has been tested with different image sequences and it works well on both indoor and outdoor scenes 1 .

2011 10th IEEE International Symposium on Mixed and Augmented Reality, 2011

Rapid 3D reconstruction of environments has become an active research topic due to the importance of 3D models in a huge number of applications, be it in Augmented Reality (AR), architecture or other commercial areas. In this paper we present a novel system that allows for the generation of a coarse 3D model of the environment within several seconds on mobile smartphones. By using a very fast and flexible algorithm a set of panoramic images is captured to form the basis of wide field-of-view images required for reliable and robust reconstruction. A cheap on-line space carving approach based on Delaunay triangulation is employed to obtain dense, polygonal, textured representations. The use of an intuitive method to capture these images, as well as the efficiency of the reconstruction approach allows for an application on recent mobile phone hardware, giving visually pleasing results almost instantly.

2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Workshops, 2010

We propose a fast image stitching and editing approach for panorama painting and have implemented it on a mobile phone. A seam search using dynamic programming finds a good boundary along which to merge the source images, and a transition smoothing process using instant image cloning removes merging artifacts, yielding highquality panoramic images. A sequential image stitching procedure requires only keeping the current source image in memory during image stitching, which saves memory and is more suitable to mobile phone implementations.

IEEE Transactions on Consumer Electronics, 2011

This paper deals with a real-time panorama algorithm for mobile camera systems. The proposed system generates the panoramic images and shows the intermediate results simultaneously on the mobile display. The proposed panorama system consists of feature point extraction, feature tracking, rotation matrix estimation, and image warping onto cylindrical surface. Feature points are extracted by fast Hessian detector in the low resolution and corner detector in the high resolution. Then, the feature points are tracked by matching between input frame and synthesized panorama image. The camera motion is modeled as a rotation matrix which is estimated using the tracked feature points. For realtime operation of panoramic image synthesis, we propose a method to estimate the rotation matrix using non-iterative least square method. We project the feature points of image onto the unit sphere surface in the world coordinates. This enables us to estimate the parameters of rotation matrix as the linear and non-iterative problem. Finally, we project the input frames onto panorama surface using the rotation matrix. We also implement a real-time display interface to show the intermediate panorama results while panorama image is being generated. Thus, the proposed panorama system paints the panorama canvas with real images. According to the experiments in the mobile systems such as mobile phone and tablet PC, the proposed system works well to generate the panoramic images in real-time.

IEEE Transactions on Consumer Electronics, 2010

We present an efficient image stitching approach for creating high-quality continuous circular 360degree panoramic images. We address the problem of color and luminance correction for long, 360-degree image sequences, where the source images have very different colors and luminance. Color matching is used for minimizing both the color differences of neighboring images and the overall color correction over the whole sequence. We perform gamma correction for the luminance component and linear correction for the chrominance components of the source images. The color consistency problem of 360-degree panoramic images is addressed by color correspondence and color difference distribution processes. We implement the stitching approach in a panoramic imaging system for creating high-resolution and high-quality panoramic images on mobile phones 1 .

This paper provides an overview of Ittiam's HDR-Panorama solution for consumer devices like smartphones and tablets. This advanced technology enables capture of high quality panorama images covering a high dynamic range of luminance. In addition to ensuring faithful capture of shadow and highlight regions, the intelligent computational photography techniques ensure seamless stitching resulting in beautiful panoramic images. Solutions for HDR-Panorama involve significant algorithmic and computational challenges. This paper describes the critical challenges addressed by Ittiam's HDR-Panorama solution. Figure 1 -Overview

ijcsit.com

– Panoramic image stitching is the process of combining multiple photographic images with overlapping fields of view to produce a panorama. First, salient features are robustly detected from the input images by a robust algorithm called Scale Invariant Feature Transform ...

2017

This paper presents an effective method in panoramic image creation. Here an automatic method of feature detection and feature mating using SIFT (Scale Invariant feature transform) algorithm has been used. SIFT algorithm is very robust method that can detect and describe local features in the image. Then find the overlapping area of these two images. A minimal cost path in the overlapping area of two images is found by dynamic programming method. This minimal-cost path (optimal seam) is used to stitch images. Dynamic programming is faster than other seam finding methods and uses little memory. The overlapping images are cut along the seam and merge together. Here there are seven steps used in image stitching which include: input image, feature detection, feature matching, image registration, computing homography using RANSAC, image warping, and finally image labeling using optimal seam.

Journal of Graphics Tools, 2002

Cylindrical panorama is being used in many applications. Cylindrical panoramic viewers render the panorama from the center of the cylinder by projecting the cylindrical map onto a planar screen. This process involves nonlinear image warping, so many panoramic viewers are implemented in software. Hardware acceleration may be used if the panorama is resampled onto the polygonal models.

2007

ABSTRACT Stitching frames from a video sequence has become a good alternative to the traditional method with only a few photographs. The big overlapping between consecutive video-frames makes it possible to construct high-quality panoramas. Most stitching methods require a vast amount of computational resources that make them not suitable for mobile devices. We present a panorama stitching method that is able to create panorama images from a video sequence.