Adaptive as-natural-as-possible image stitching

Lin, Chung-Ching; Pankanti, Sharathchandra; Ramamurthy, Karthikeyan Natesan; Aravkin, Aleksandr Y.

doi:10.1109/cvpr.2015.7298719

Cited by 280 publications

(212 citation statements)

References 14 publications

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“…It is a similar approach to the bundle adjustment method employed in the structure-from-motion (SFM) pipeline. The latest image-based approach in [18] aims to handle large parallax, while our work emphasizes the case of a large number of images of approximately planar scenes.…”

Section: Introductionmentioning

confidence: 99%

Mosaicking of Unmanned Aerial Vehicle Imagery in the Absence of Camera Poses

et al. 2016

Remote Sensing

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Abstract:The mosaicking of Unmanned Aerial Vehicle (UAV) imagery usually requires information from additional sensors, such as Global Position System (GPS) and Inertial Measurement Unit (IMU), to facilitate direct orientation, or 3D reconstruction approaches (e.g., structure-from-motion) to recover the camera poses. In this paper, we propose a novel mosaicking method for UAV imagery in which neither direct nor indirect orientation procedures are required. Inspired by the embedded deformation model, a widely used non-rigid mesh deformation model, we present a novel objective function for image mosaicking. Firstly, we construct a feature correspondence energy term that minimizes the sum of the squared distances between matched feature pairs to align the images geometrically. Secondly, we model a regularization term that constrains the image transformation parameters directly by keeping all transformations as rigid as possible to avoid global distortion in the final mosaic. Experimental results presented herein demonstrate that the accuracy of our method is twice as high as an existing (purely image-based) approach, with the associated benefits of significantly faster processing times and improved robustness with respect to reference image selection.

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Section: Introductionmentioning

confidence: 99%

Mosaicking of Unmanned Aerial Vehicle Imagery in the Absence of Camera Poses

et al. 2016

Remote Sensing

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“…Zhang et al, [12] proposed parallax tolerant image stitching method by locally formulating image warping problem as a mesh warping problem. Lin et al, [13] used local projective transformation and a global similarity transformation on non-overlapping regions. All these models attempted to use locally non-linear warping to get more natural panoramas.…”

Section: Related Workmentioning

confidence: 99%

Robust Multi-homography Method for Image Stitching under Large Viewpoint Changes

Yan¹,

Liu²,

Peng³

2017

IJHIT

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“…The combination of a projective transform and a similarity transform is advocated to ameliorate structure distortion during warping [CSC14]. To alleviate the projective distortion, Lin et al [LPRA15] combined a linearized local homography with a global similarity transform. To alleviate the projective distortion, Lin et al [LPRA15] combined a linearized local homography with a global similarity transform.…”

Section: Related Workmentioning

confidence: 99%

Re‐Compositable Panoramic Selfie with Robust Multi‐Frame Segmentation and Stitching

Wang

Liu

et al. 2016

Computer Graphics Forum

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Figure 1: We created a panoramic selfie that not only has a much wider background coverage, but also is re-compositable under different user-selected foreground position. AbstractIt is a challenging task for ordinary users to capture selfies with a good scene composition, given the limited freedom to position the camera. Creative hardware (e.g., selfie sticks) and software (e.g., panoramic selfie apps) solutions have been proposed to extend the background coverage of a selife, but to achieve a perfect composition on the spot when the selfie is captured remains to be difficult. In this paper, we propose a system that allows the user to shoot a selfie video by rotating the body first, then produce a final panoramic selfie image with user-guided scene composition as postprocessing. Our key technical contribution is a fully automatic, robust multi-frame segmentation and stitching framework that is tailored towards the special characteristics of selfie images. We analyze the sparse feature points and employ a spatial-temporal optimization for bilayer feature segmentation, which leads to more reliable background alignment than previous image stitching techniques. The sparse classification is then propagated to all pixels to create dense foreground masks for person-background composition. Finally, based on a user-selected foreground position, our system uses content-preserving warping to produce a panoramic seflie with minimal distortion to the face region. Experimental results show that our approach can reliably generate high quality panoramic selfies, while a simple combination of previous image stitching and segmentation approaches often fails.

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Adaptive as-natural-as-possible image stitching

Cited by 280 publications

References 14 publications

Mosaicking of Unmanned Aerial Vehicle Imagery in the Absence of Camera Poses

Mosaicking of Unmanned Aerial Vehicle Imagery in the Absence of Camera Poses

Robust Multi-homography Method for Image Stitching under Large Viewpoint Changes

Re‐Compositable Panoramic Selfie with Robust Multi‐Frame Segmentation and Stitching

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