&lt;title&gt;Generating panorama photos&lt;/title&gt;

Deng, Yining; Zhang, Tong

doi:10.1117/12.513119

Cited by 15 publications

(11 citation statements)

References 12 publications

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“…There are two popular ways of blending the images [10]. One is called alpha "feathering" blending, which takes weighted average of two images.…”

Section: Blendingmentioning

confidence: 99%

Image Stitching based on Feature Extraction Techniques: A Survey

Adel¹,

Elmogy²,

El-Bakry³

2014

IJCA

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Image stitching (Mosaicing) is considered as an active research area in computer vision and computer graphics. Image stitching is concerned with combining two or more images of the same scene into one high resolution image which is called panoramic image. Image stitching techniques can be categorized into two general approaches: direct and feature based techniques. Direct techniques compare all the pixel intensities of the images with each other, whereas feature based techniques aim to determine a relationship between the images through distinct features extracted from the processed images. The last approach has the advantage of being more robust against scene movement, faster, and has the ability to automatically discover the overlapping relationships among an unordered set of images. The purpose of this paper is to present a survey about the feature based image stitching. The main components of image stitching will be described. A framework of a complete image stitching system based on feature based approaches will be introduced. Finally, the current challenges of image stitching will be discussed.

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“…There are two popular ways of blending the images [10]. One is called alpha "feathering" blending, which takes weighted average of two images.…”

Section: Blendingmentioning

confidence: 99%

Image Stitching based on Feature Extraction Techniques: A Survey

Adel¹,

Elmogy²,

El-Bakry³

2014

IJCA

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“…The first group includes the works Refs. [1], [3], [5], [9], which are based on global transformations such as homography. The second group includes the works Refs.…”

Section: Related Workmentioning

confidence: 99%

Real-time Video Mosaicing using Non-rigid Registration

Souza

Okutomi

Torii

2012

IPSJ Transactions on Computer Vision and Applications

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This paper presents a real-time incremental mosaicing method that generates a large seamless 2D image by stitching video key-frames as soon as they are detected. There are four main contributions: (1) we propose a "fast" key-frame selection procedure based solely on the distribution of the distance of matched feature descriptors. This procedure automatically selects key-frames that are used to expand the mosaics while achieving real-time performance; (2) we register key-frame images by using a non-rigid deformation model based on a triangular mesh in order to "smoothly" stitch images when scene transformations can not be expressed by homography; (3) we add a new constraint on the non-rigid deformation model that penalizes over-deformation in order to create mosaics with natural appearance; (4) we propose a fast image stitching algorithm for real-time mosaic rendering modeled as an instance of the minimum graph cut problem, applied to mesh triangles instead of the image pixels. The performance of the proposed method is validated by experiments in non-controlled conditions and by comparison with a state-of-the-art method.

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“…These works can be grouped in 3 classes: (1) offline methods that use homography or lower degree transformations, (2) offline methods that use higher degree transformations, and (3) online methods. The group (1) includes the works, [2,9,12,7], which are based on global transformations such as homography. The group (2) includes the works [4,3], which model the deformation as quadratic functions.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Image Mosaicing Using Non-rigid Registration

Souza

Okutomi

Torii

2011

Advances in Image and Video Technology

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Abstract. Mosaicing is a classical application of image registration where images from the same scene are stitched together to generate a larger seamless image. This paper presents a real-time incremental mosaicing method that generates 2D mosaics by stitching video key-frames as soon as they are detected. The contributions are three-fold: (1) we propose a "fast" key-frame selection procedure based solely on the distribution of the distance of matched feature descriptors. This procedure automatically selects key-frames that are used to expand the mosaics while achieving real-time performance; (2) we register key-frame images by using a non-rigid deformation model in order to "smoothly" stitch images when scene transformations can not be expressed by homography: (3) we add a new constraint on the non-rigid deformation model that penalizes over-deformation in order to create "visually natural" mosaics. The performance of the proposed method was validated by experiments in non-controlled conditions and by comparison with the state-of-the-art method.

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<title>Generating panorama photos</title>

Cited by 15 publications

References 12 publications

Image Stitching based on Feature Extraction Techniques: A Survey

Image Stitching based on Feature Extraction Techniques: A Survey

Real-time Video Mosaicing using Non-rigid Registration

Real-Time Image Mosaicing Using Non-rigid Registration

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