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Seam carving for content-aware image resizing

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Ariel ShamirAuthors Info & Claims

SIGGRAPH '07: ACM SIGGRAPH 2007 papers

Pages 10 - es

https://doi.org/10.1145/1275808.1276390

Published: 29 July 2007 Publication History

Abstract

Effective resizing of images should not only use geometric constraints, but consider the image content as well. We present a simple image operator called seam carving that supports content-aware image resizing for both reduction and expansion. A seam is an optimal 8-connected path of pixels on a single image from top to bottom, or left to right, where optimality is defined by an image energy function. By repeatedly carving out or inserting seams in one direction we can change the aspect ratio of an image. By applying these operators in both directions we can retarget the image to a new size. The selection and order of seams protect the content of the image, as defined by the energy function. Seam carving can also be used for image content enhancement and object removal. We support various visual saliency measures for defining the energy of an image, and can also include user input to guide the process. By storing the order of seams in an image we create multi-size images, that are able to continuously change in real time to fit a given size.

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Cited By

Rajaram SNuman NKumaravel BMarquardt NWilson A(2024)BlendScape: Enabling End-User Customization of Video-Conferencing Environments through Generative AIProceedings of the 37th Annual ACM Symposium on User Interface Software and Technology10.1145/3654777.3676326(1-19)Online publication date: 13-Oct-2024
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Index Terms

Seam carving for content-aware image resizing
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision representations
        Image representations
  2. Computer graphics

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cover image ACM Conferences

SIGGRAPH '07: ACM SIGGRAPH 2007 papers

August 2007

1019 pages

ISBN:9781450378369

DOI:10.1145/1275808

Conference Chair:
Marc Levoy

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

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Published: 29 July 2007

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SIGGRAPH07: Special Interest Group on Computer Graphics and Interactive Techniques Conference

August 5 - 9, 2007

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SIGGRAPH '07 Paper Acceptance Rate 108 of 455 submissions, 24%;

Overall Acceptance Rate 1,822 of 8,601 submissions, 21%

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Cited By

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https://dl.acm.org/doi/10.1145/3654777.3676326
Arora JMuller SAcar U(2024)Disentanglement with Futures, State, and InteractionProceedings of the ACM on Programming Languages10.1145/36328958:POPL(1569-1599)Online publication date: 5-Jan-2024
https://dl.acm.org/doi/10.1145/3632895
Zhang WKam-Kwai WChen YJia AWang LZhang JCheng LQu HChen W(2024)ScrollTimes: Tracing the Provenance of Paintings as a Window Into HistoryIEEE Transactions on Visualization and Computer Graphics10.1109/TVCG.2024.338852330:6(2981-2994)Online publication date: 16-Apr-2024
https://dl.acm.org/doi/10.1109/TVCG.2024.3388523
Xiao RXu YXu FHou ZZhang HChen S(2024)LSFP-Tracker: An Autonomous Laser Stripe Feature Point Extraction Algorithm Based on Siamese Network for Robotic Welding Seam TrackingIEEE Transactions on Industrial Electronics10.1109/TIE.2023.324326571:1(1037-1048)Online publication date: Jan-2024
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Imani HIslam M(2024)Spatio-Temporal Consistent Non-homogeneous Extreme Video Retargeting2024 IEEE International Conference on Consumer Electronics (ICCE)10.1109/ICCE59016.2024.10444165(1-6)Online publication date: 6-Jan-2024
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Nithin Skantha MMeghadharsan BSri Vignesh CThiruselvan JAnuragi A(2024)Octopus: A Latent Diffusion Model for Enhanced Text-Driven Manipulation in Image Synthesis2024 IEEE International Conference on Computer Vision and Machine Intelligence (CVMI)10.1109/CVMI61877.2024.10782008(1-8)Online publication date: 19-Oct-2024
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