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Bibliography [chapter]

Scott Krig
2014 Computer Vision Metrics  
Computer Vision and Image Understanding Volume 110, Issue 3, June 2008, Pages 346-359. 161. Lowe, David G. "SIFT Distinctive Image Features from Scale-Invariant Keypoints."  ...  Bretzner, L., and T. Lindeberg. "Feature Tracking with Automatic Selection of Spatial Scales." Computer Vision and Image Understanding Volume 71, Issue 3, September 1998, Pages 385-392. 211.  ... 
doi:10.1007/978-1-4302-5930-5_13 fatcat:bnsbslueindjrdsxjvt5ulcozq

Recognition of adult images, videos, and web page bags

Weiming Hu, Haiqiang Zuo, Ou Wu, Yunfei Chen, Zhongfei Zhang, David Suter
2011 ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)  
Computer Vision and Image Understanding, 102(2):214-226, 2006. [23] K. Schindler and D. Suter. Two-view multibody structure-and-motion with outliers through model selection. IEEE Trans.  ...  Visual learning and recognition of sequential data manifolds with applications to human movement analysis. Computer Vision and Image Understanding, 110(2):153-172, May 2008. [16] T-J. Chin and D.  ... 
doi:10.1145/2037676.2037685 fatcat:6fflafayhnbwviiss6x7y7xo4u

RESPONSE: Collaboration and Collegiality: The Dual Pillars of Cardiovascular Imaging Now and in the Future

Christopher M Kramer
2018 JACC Cardiovascular Imaging  
Parwani and colleagues have laid out an important vision of the future of cardiovascular imaging, especially for fellows-in-training and early career cardiologists.  ...  Cardiologists will be referring their patients for imaging procedures and understand the underlying clinical scenarios and pathophysiology.  ... 
doi:10.1016/j.jcmg.2018.10.005 pmid:30409332 fatcat:ysvmn5slznb3jjsdlip24bdrna

Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches

M. Zhou, J. Scott, B. Chaudhury, L. Hall, D. Goldgof, K.W. Yeom, M. Iv, Y. Ou, J. Kalpathy-Cramer, S. Napel, R. Gillies, O. Gevaert (+1 others)
2017 American Journal of Neuroradiology  
We review brain tumor radiologic studies (eg, imaging interpretation) through computational models (eg, computer vision and machine learning) that provide novel clinical insights.  ...  Radiomics describes a broad set of computational methods that extract quantitative features from radiographic images.  ...  approaches in radiology, computer vision, and machine learning.  ... 
doi:10.3174/ajnr.a5391 pmid:28982791 pmcid:PMC5812810 fatcat:fovsdrilurg4xp7ghpjimk7pge

Intelligent Visual Media Processing: When Graphics Meets Vision

Ming-Ming Cheng, Qi-Bin Hou, Song-Hai Zhang, Paul L. Rosin
2017 Journal of Computer Science and Technology  
understanding and 3D model analysis.  ...  The computer graphics and computer vision communities have been working closely together in recent years, and a variety of algorithms and applications have been developed to analyze and manipulate the  ...  This research was sponsored by NSFC (NO. 61572264), Huawei Innovation Research Program (HIRP), CAST young talents plan, and Tianjin Short-term Recruitment Program of Foreign Experts.  ... 
doi:10.1007/s11390-017-1681-7 fatcat:j6u7dzfbhfgnlpnluqajjbaxy4

A combinatorial algorithm to construct 3D isothetic covers

Nilanjana Karmakar, Arindam Biswas, Partha Bhowmick, Bhargab B. Bhattacharya
2013 International Journal of Computer Mathematics  
Chattopadhyay and B. N. Chatterji): Dig-2013 ital Geometry in Image Processing. CRC Press. Journals [2] Forthcoming a (with S.  ...  Pal): Fast circular arc segmentation based on approximate circu-Forthcoming larity and cuboid graph. [3] Forthcoming b (with R.  ...  In: Electronic Letters on Computer Vision and Image Analysis (ELCVIA) 7, No. 2, pp. 76-95. [24] 2007 (with B. B.  ... 
doi:10.1080/00207160.2012.734813 fatcat:sif37qpcnzdvhlzlpbsw26wr7e

FloodNet: A High Resolution Aerial Imagery Dataset for Post Flood Scene Understanding

Maryam Rahnemoonfar, Tashnim Chowdhury, Argho Sarkar, Debvrat Varshney, Masoud Yari, Robin Murphy
2021 IEEE Access  
research areas in computer vision and an essential part of scene understanding.  ...  ROBIN ROBERSON MURPHY received a B.M.E. in mechanical engineering, a M.S. and Ph.D. in computer science in VOLUME 4, 2016 VOLUME 4, 2016 VOLUME 4, 2016 VOLUME 4  ... 
doi:10.1109/access.2021.3090981 fatcat:wacd4jsapzfuhhu5kjvkl3ab2m

Front Matter [chapter]

Jack N. Sanders-Reed
2021 Principles of Vision-Enabled Autonomous Flight  
This includes: • Managers who may need to understand how and why vision systems are required for most autonomous flight scenarios. • System engineers who must understand the strengths, limitations, and  ...  requirements for vision systems. • Sensor system engineers who must select sensor suites, architectures, and algorithms. • Regulators who must understand what can and cannot be expected from sensing systems  ... 
doi:10.1117/3.2603090.fm fatcat:x7qe6lp6v5hahkyybe6lwuid6a

AutoCloud+, a "Universal" Physical and Statistical Model-Based 2D Spatial Topology-Preserving Software for Cloud/Cloud–Shadow Detection in Multi-Sensor Single-Date Earth Observation Multi-Spectral Imagery—Part 1: Systematic ESA EO Level 2 Product Generation at the Ground Segment as Broad Context

Andrea Baraldi, Dirk Tiede
2018 ISPRS International Journal of Geo-Information  
Never accomplished to date in an operating mode by any EO data provider at the ground segment, systematic ESA EO Level 2 product generation is an inherently ill-posed computer vision (CV) problem (chicken-and-egg  ...  quality layers detection in multi-sensor, multi-temporal and multi-angular EO big data cubes characterized by the five Vs, namely, volume, variety, veracity, velocity and value.  ...  The authors wish to thank the Editor-in-Chief, Associate Editor and reviewers for their competence, patience and willingness to help.  ... 
doi:10.3390/ijgi7120457 fatcat:frhng3wbffct5ltnnv6trzofea

Binary Image Features Proposed to Empower Computer Vision [article]

Soumi Ray, Vinod Kumar
2018 arXiv   pre-print
This literature has proposed three fast and easy computable image features to improve computer vision by offering more human-like vision power.  ...  This capacity of getting an idea at a glance is analysed and three basic features are proposed to empower computer vision.  ...  Acknowledgement Authors would like to thank the host institute for the laboratory, internet and other essential facilities to conduct the research.  ... 
arXiv:1808.08275v1 fatcat:wctj3f6hxfczdnr6kjswkuadgq

Guiding Monocular Depth Estimation Using Depth-Attention Volume [article]

Lam Huynh, Phong Nguyen-Ha, Jiri Matas, Esa Rahtu, Janne Heikkila
2020 arXiv   pre-print
This is achieved by incorporating a non-local coplanarity constraint to the network with a novel attention mechanism called depth-attention volume (DAV).  ...  Recovering the scene depth from a single image is an ill-posed problem that requires additional priors, often referred to as monocular depth cues, to disambiguate different 3D interpretations.  ...  .: Sun rgb-d: A rgb-d scene understanding benchmark suite. In: Proceedings of the IEEE conference on computer vision and pattern recognition. pp. 567-576 (2015) 32.  ... 
arXiv:2004.02760v2 fatcat:rbev26l6zndj5jui777b2b46qy

Deep Learning for Object Detection and Segmentation in Videos: Toward an Integration With Domain Knowledge

Athina Ilioudi, Azita Dabiri, Ben J. Wolf, Bart De Schutter
2022 IEEE Access  
Deep learning has enabled the rapid expansion of computer vision tasks from image frames to video segments.  ...  This paper focuses on the review of the latest research in the field of computer vision tasks in general and on object localization and identification of their associated pixels in video frames in particular  ...  computer vision.  ... 
doi:10.1109/access.2022.3162827 fatcat:jdaz4brwgrhwrdbmzwqh7dg3wu

Current research opportunities of image processing and computer vision

Abhishek Gupta
2019 Computer Science  
Image processing and computer vision is an important and essential area in today's scenario. Several problems can be solved through computer vision techniques.  ...  This article is targeted to the research students, scholars and researchers who are interested to solve the problems in the field of image processing and computer vision.  ...  and medical domain that can be solved through the concept of image processing and computer vision.  ... 
doi:10.7494/csci.2019.20.4.3163 fatcat:7rexjkhlkfes7kavgjtaly2nyy

Guest Editors' Introduction to the Special Issue on RGB-D Vision: Methods and Applications

Mohammed Bennamoun, Yulan Guo, Federico Tombari, Kamal Youcef-Toumi, Ko Nishino
2020 IEEE Transactions on Pattern Analysis and Machine Intelligence  
Ç R GB-D vision is an emerging research topic in computer vision, with a number of applications in robotics, entertainment, biometrics and multimedia.  ...  As guest editors of this special issue on "RGB-D Vision: Methods and Applications", we were happy to receive 76 submissions to our special issue.  ...  Processing (ICASSP) and European Conference on Computer Vision (ECCV).  ... 
doi:10.1109/tpami.2020.2976227 fatcat:dqt5dt3ymnesfikmgu2sxffdcu

Multi-Faceted Hierarchical Image Segmentation Taxonomy ( MFHIST)

Tilottama Goswami, Arun Agarwal, C Raghavendra Rao
2021 IEEE Access  
An abundance of various segmentation techniques are available in the literature, that cater to wide range of image understanding applications.  ...  The other segmentation approaches have not been considered here, owing to the enormous volume of works in the past four to five decades and limitation in articulating all of them using MFHIST.  ...  The new approach cater to computer vision and understanding tasks, such as scene classification, object detection and recognition [80] etc.  ... 
doi:10.1109/access.2021.3055678 fatcat:r3aaee4vrbgqhdzlb6qc5vkefy
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