Journal ArticleDOI
Image change detection algorithms: a systematic survey
TLDR
In this paper, the authors present a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling.Abstract:
Detecting regions of change in multiple images of the same scene taken at different times is of widespread interest due to a large number of applications in diverse disciplines, including remote sensing, surveillance, medical diagnosis and treatment, civil infrastructure, and underwater sensing. This paper presents a systematic survey of the common processing steps and core decision rules in modern change detection algorithms, including significance and hypothesis testing, predictive models, the shading model, and background modeling. We also discuss important preprocessing methods, approaches to enforcing the consistency of the change mask, and principles for evaluating and comparing the performance of change detection algorithms. It is hoped that our classification of algorithms into a relatively small number of categories will provide useful guidance to the algorithm designer.read more
Citations
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Journal ArticleDOI
Tutorial: Dealing with rotation matrices and translation vectors in image-based applications: A tutorial
TL;DR: This tutorial aims to describe and solve the main factors that generate the ambiguity in using rotation matrices and to permit dealing with them properly both in theory and in practice.
Proceedings ArticleDOI
Creating panoramas on mobile phones
TL;DR: This work presents a novel panorama stitching method that is designed to create high-quality image mosaics from both video clips and separate images even on low-resource devices.
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Domain-Transformable Sparse Representation for Anomaly Detection in Moving-Camera Videos
TL;DR: Results obtained from a comprehensive video database acquired with moving cameras on a visually cluttered environment indicate that the proposed algorithm provides a better geometric registration between reference and target videos, greatly improving the overall performance of the anomaly-detection system.
Journal ArticleDOI
Application of Gibbs---Markov random field and Hopfield-type neural networks for detecting moving objects from video sequences captured by static camera
TL;DR: A moving objects detection scheme using Gibbs–Markov random field (GMRF) and Hopfield-type neural network (HTNN) in expectation maximization (EM) framework for video sequences captured by static camera and is compared with those of the codebook-based background subtraction and GMRF model with graph-cut schemes.
Proceedings ArticleDOI
Subpixel Change Detection Based on Abundance and Slope Features
TL;DR: The preliminary result shows that the subpixel change detection method can provide more detailed information about landslide spread than pixel-based change detection algorithms.
References
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Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Journal ArticleDOI
Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
Stuart Geman,Donald Geman +1 more
TL;DR: The analogy between images and statistical mechanics systems is made and the analogous operation under the posterior distribution yields the maximum a posteriori (MAP) estimate of the image given the degraded observations, creating a highly parallel ``relaxation'' algorithm for MAP estimation.
Book
Multiple view geometry in computer vision
Richard Hartley,Andrew Zisserman +1 more
TL;DR: In this article, the authors provide comprehensive background material and explain how to apply the methods and implement the algorithms directly in a unified framework, including geometric principles and how to represent objects algebraically so they can be computed and applied.
Journal ArticleDOI
Fundamentals of statistical signal processing: estimation theory
TL;DR: The Fundamentals of Statistical Signal Processing: Estimation Theory as mentioned in this paper is a seminal work in the field of statistical signal processing, and it has been used extensively in many applications.
Journal ArticleDOI
Image registration methods: a survey
Barbara Zitová,Jan Flusser +1 more
TL;DR: A review of recent as well as classic image registration methods to provide a comprehensive reference source for the researchers involved in image registration, regardless of particular application areas.