IP Library › Granted Patent US 11,875,490
Granted Patent B2
US 11,875,490 · App. 17/558,969 · Granted Jan 16, 2024

Method and apparatus for stitching images

Inventors: Yeejin Lee (Seoul, KR); Byeongkeun Kang (Seoul, KR); Seongyeop Yang (Seoul, KR); Taeha Kim (Hwaseong-si, KR)
Assignee: Foundation for Research and Business, Seoul National University of Science and Technology
G06T5/50G06T7/30G06V10/40G06T2207/20084G06T2207/20221
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Quick Facts
Patent No.
US 11,875,490
App. No.
17/558,969
Granted
Jan 16, 2024
Kind
B2
Abstract

An image stitching method and apparatus are disclosed. The image stitching apparatus includes at least one processor and a memory. The processor may obtain a plurality of images at different viewpoints, estimate homographies of each of the plurality of images, generate an aligned image by aligning the plurality of images based on the homographies of each of the plurality of images, obtain a collective energy map by inputting the aligned image to a neural network, estimate a stitching line of the aligned image based on the collective energy map, and generate a stitched image by blending the aligned image based on the stitching line.

Claims (28)

1. An image stitching method, comprising:

obtaining a plurality of images at different viewpoints;

estimating homographies of the plurality of images;

generating an aligned image by aligning the plurality of images based on the homographies of each of the plurality of images;

obtaining a collective energy map by inputting the aligned image to a neural network;

estimating a stitching line of the aligned image based on the collective energy map; and

generating a stitched image by blending the aligned image based on the stitching line,

wherein the collective energy map combines an energy map using a gradient, an energy map using a motion, an energy map using object segmentation, and an energy map using distance transformation of object segmentation, and

wherein the image stitching method estimates the stitching line as a path having a minimum energy or a maximum energy.

2. The method of claim 1 , wherein the obtaining of the collective energy map comprises:

extracting feature information from the aligned image; and

calculating an energy for each pixel of the aligned image based on the feature information.

3. The method of claim 1 , wherein the neural network is configured to:

estimate an estimated energy map from a training image of a different viewpoint and learn to minimize a loss between the estimated energy map and a ground truth energy map.

4. The method of claim 3 , wherein the estimated energy map and the ground truth energy map comprises:

the energy map using the gradient of the training image of the different viewpoint, the energy map using the motion of an object between frames, or the energy map using the object segmentation.

5. An image stitching apparatus, comprising:

at least one processor; and

a memory,

wherein the processor is configured to:

obtain a plurality of images at different viewpoints;

estimate homographies of the plurality of images;

generate an aligned image by aligning the plurality of images based on the homographies of each of the plurality of images;

obtain a collective energy map by inputting the aligned image to a neural network;

estimate a stitching line of the aligned image based on the collective energy map; and

generate a stitched image by blending the aligned image based on the stitching line,

wherein the collective energy map combines an energy map using a gradient, an energy map using a motion, an energy map using object segmentation, and an energy map using distance transformation of object segmentation, and

wherein the image stitching apparatus estimates the stitching line as a path having a minimum energy or a maximum energy.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Dec 22, 2021
From: LEE, YEEJIN; KANG, BYEONGKEUN; YANG, SEONGYEOP; KIM, TAEHA
To: FOUNDATION FOR RESEARCH AND BUSINESS, SEOUL NATIONAL UNIVERSITY OF SCIENCE AND TECHNOLOGY
Reel/Frame 058459/0126 →
Priority Claims (1)
KR 10-2020-0186308 · Dec 29, 2020 · national
Continuity (1)
Related Publication 20220207679A1 · Jun 30, 2022
Cited By (2)
US 12,705,690 US 12,718,471