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Benchmarking neuromorphic vision: lessons learnt from computer vision

Cheston Tan, Stephane Lallee, Garrick Orchard
2015 Frontiers in Neuroscience  
We are presented with a unique opportunity to shape the development of Neuromorphic Vision benchmarks and challenges by leveraging what has been learnt from the use of datasets in frame-based computer  ...  Taking advantage of this opportunity, in this paper we review the role that benchmarks and challenges have played in the advancement of frame-based computer vision, and suggest guidelines for the creation  ...  We use the term "Computer Vision" (CV) to denote the conventional approach to visual sensing, which begins with acquisition of images (photographs), or sequences of images (video).  ... 
doi:10.3389/fnins.2015.00374 pmid:26528120 pmcid:PMC4602133 fatcat:khp34bi26reg7mnzgn7pvxq6ye

SteReFo: Efficient Image Refocusing with Stereo Vision

Benjamin Busam, Matthieu Hog, Steven McDonagh, Gregory Slabaugh
2019 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)  
We present a general approach that utilizes stereo vision to refocus images and videos (cf. Fig. 1 ).  ...  It also enables computational video focus tracking for moving objects in addition to refocusing of static images.  ...  Barron et al. [4] propose to utilize structural metrics to quantify image quality with a light field ground truth.  ... 
doi:10.1109/iccvw.2019.00411 dblp:conf/iccvw/BusamHMS19 fatcat:7oxfmmmgd5afjaaq4aztngcbye

SteReFo: Efficient Image Refocusing with Stereo Vision [article]

Benjamin Busam and Matthieu Hog and Steven McDonagh and Gregory Slabaugh
2019 arXiv   pre-print
It also enables computational video focus tracking for moving objects in addition to refocusing of static images.  ...  Whether to attract viewer attention to a particular object, give the impression of depth or simply reproduce human-like scene perception, shallow depth of field images are used extensively by professional  ...  Barron et al. [4] propose to utilize structural metrics to quantify image quality with a light field ground truth.  ... 
arXiv:1909.13395v1 fatcat:pygdnjn3pre3hj2dlynu5ftkim

Computer vision tracking of stemness

Kang Li, Eric D. Miller, Mei Chen, Takeo Kanade, Lee E. Weiss, Phil G. Campbell
2008 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro  
Towards this goal, we are developing a computer vision based system to automatically and reliably follow the behaviors of individual stem cells in expanding populations.  ...  This paper reports on significant progress in our development. In particular, we present a machine-learning approach for detecting spatiotemporal mitosis events without image segmentation.  ...  To realize these much-needed toolsets, we are developing a computer vision based cell tracking system that can track each and every cell in a dynamic and expanding population imaged with phase-contrast  ... 
doi:10.1109/isbi.2008.4541129 dblp:conf/isbi/LiMCKWC08 fatcat:dp73z5cgyjbzdkzim27ta4jalq

A Cognitive Vision Approach to Image Segmentation [chapter]

Vincent Martin, Monique Thonnat
2008 Tools in Artificial Intelligence  
Finally, in many computer vision systems at the detection layer, the goal is to separate the object(s) of interest from the image background.  ...  Section 2 introduces the reader to image segmentation in the context of computer vision systems. We propose an overview on topics closely related to our problem.  ...  How to reference In order to correctly reference this scholarly work, feel free to copy and paste the following: Vincent Martin and Monique Thonnat (2008) .  ... 
doi:10.5772/6080 fatcat:zwbnmefhnvhvbiwd6qgapdofxa

Motion vision based structure estimation in forest environment

Jakke Kulovesi
2009 2009 IEEE/RSJ International Conference on Intelligent Robots and Systems  
The results show that dense optical flow can be computed from a real-world forest data accurately enough as to enable instantaneous dense structure estimates of the visible image scene.  ...  Based on the measurements, tree cutting could be optimized and harvester automation increased, resulting in higher resource utilization efficiency.  ...  From an image object segmentation point of view alone, the results are good, providing a possible solution to a generally very difficult computer vision problem.  ... 
doi:10.1109/iros.2009.5353961 dblp:conf/iros/Kulovesi09 fatcat:qg3gnifpdbca3f3ipwpfk7utem

Predicting Through-Focus Visual Acuity with the Eye's Natural Aberrations

Amanda C. Kingston, Ian G. Cox
2013 Optometry and Vision Science  
To develop a predictive optical modeling process that utilizes individual computer eye models along with a novel through-focus image quality metric. Methods.  ...  With this high correlation (R 2 Q 0.90) and high level of predictability, more design options can be explored in the computer to optimize performance before a lens is manufactured and tested clinically  ...  Pupil plane metrics are defined by the quality of the shape of the wave aberrations in the pupil plane, whereas image plane metrics utilize the point spread function (PFS) or optical transfer function.  ... 
doi:10.1097/opx.0000000000000031 pmid:24013796 fatcat:lffdn3spnvhzlaugdfjipwaf5u

Perceptual Annotation: Measuring Human Vision to Improve Computer Vision

Walter J. Scheirer, Samuel E. Anthony, Ken Nakayama, David D. Cox
2014 IEEE Transactions on Pattern Analysis and Machine Intelligence  
For many problems in computer vision, human learners are considerably better than machines.  ...  A key intuition for this approach is that while it may remain infeasible to dramatically increase the amount of data and high-quality labels available for the training of a given system, measuring the  ...  Anthony contributed equally to this work.  ... 
doi:10.1109/tpami.2013.2297711 pmid:26353347 fatcat:25xqb43n5rbjbitoxbjhh2xada

An improved real-time miniaturized embedded stereo vision system (MESVS-II)

Bahador Khaleghi, Siddhant Ahuja, Q. M. Jonathan Wu
2008 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops  
This is a significant improvement over the original MESVS-I system in terms of performance, quality and accuracy of results.  ...  management, in-place processing scheme, code optimization, and the pipelinedprogramming model that takes advantage of the dual-core architecture of the embedded processor.  ...  Acknowledgements The work is supported in part by the CRC program, the NSERC Discovery Grant, and the AUTO21 NCE.  ... 
doi:10.1109/cvprw.2008.4563144 dblp:conf/cvpr/KhaleghiAW08 fatcat:rcd6wnibzvhm3ceq5vtlv3i6di

Computer Vision User Entity Behavior Analytics [article]

Sameer Khanna
2021 arXiv   pre-print
Combined, they form Computer Vision User and Entity Behavior Analytics, a detection system designed from the ground up to improve upon advancements in academia and mitigate the issues that prevent the  ...  Seeking to improve detection of such threats, we develop novel techniques to enable us to extract powerful features, generate high quality image encodings, and augment attack vectors for greater classification  ...  In order to evaluate this design, we quantify the colorfulness of an image via the colourfulness metric [31] .  ... 
arXiv:2111.13176v2 fatcat:sjfvbqpojzetldktuybnocoxhm

Tensor-to-Image: Image-to-Image Translation with Vision Transformers [article]

Yiğit Gündüç
2021 arXiv   pre-print
In this paper, we utilized a vision transformer-based custom-designed model, tensor-to-image, for the image to image translation.  ...  Transformers start to take over all areas of deep learning and the Vision transformers paper also proved that they can be used for computer vision tasks.  ...  There have been attempts to utilize transformers like self-attention-based architectures with CNNs for computer vision tasks [11, 12, 13, 18, 19] .  ... 
arXiv:2110.08037v1 fatcat:5z7g2m5kyfg67g62nlvyrkl6cy

A Survey of Learning Approaches and Application for 3D Vision

Luanhao Lu, J. Heled, A. Yuan
2018 MATEC Web of Conferences  
Three-dimensional (3D) vision extracted from the stereo images or reconstructed from the twodimensional (2D) images is the most effective topic in computer vision and video surveillance.  ...  The paper focuses on 3D vision, introduce the background and process of 3D vision, reviews several classical datasets in the field of 3D vision, based on which the learning approaches and several types  ...  Muhalmann et al. represents a method which uses SAD correlation metric for color images, utilizing left to right reliability check with the aim of achieving improvement in both the fields of speed and  ... 
doi:10.1051/matecconf/201817303053 fatcat:5rgw7t6cnfgrrdjfxtd2jzh5lu

Fashion Meets Computer Vision: A Survey [article]

Wen-Huang Cheng, Sijie Song, Chieh-Yun Chen, Shintami Chusnul Hidayati, Jiaying Liu
2021 arXiv   pre-print
Fashion, mainly conveyed by vision, has thus attracted much attention from computer vision researchers in recent years.  ...  Fashion is the way we present ourselves to the world and has become one of the world's largest industries.  ...  [114] computed the NDCG that measures how close the ranking of the top-k recommended styles is to the optimal ranking.  ... 
arXiv:2003.13988v2 fatcat:ajzvyn4ck5gqxk5ht5u3mrdmba

Geodesic Methods in Computer Vision and Graphics

Gabriel Peyré
2009 Foundations and Trends in Computer Graphics and Vision  
This review paper is intended to give an updated tour of both foundations and trends in the area of geodesic methods in vision and graphics.  ...  In particular, the reader should refer to [42, 147, 208, 209, 213, 255] for fascinating applications of these methods to many important problems in vision and graphics.  ...  To approximate images with step edges, or noisy images, the computation of the optimal metric requires a prior smoothing of the image, and the amount of smoothing depends on the noise level and the number  ... 
doi:10.1561/0600000029 fatcat:oe2kxm2lofff7gsqn4f7yraa4i

Are we ready for autonomous driving? The KITTI vision benchmark suite

A. Geiger, P. Lenz, R. Urtasun
2012 2012 IEEE Conference on Computer Vision and Pattern Recognition  
Our goal is to reduce this bias by providing challenging benchmarks with novel difficulties to the computer vision community. Our benchmarks are available online at:  ...  Our benchmarks comprise 389 stereo and optical flow image pairs, stereo visual odometry sequences of 39.2 km length, and more than 200k 3D object annotations captured in cluttered scenarios (up to 15 cars  ...  We further ensure that images from one sequence do not appear in both training and test set. Evaluation Metrics We evaluate state-of-the-art approaches utilizing a diverse set of metrics.  ... 
doi:10.1109/cvpr.2012.6248074 dblp:conf/cvpr/GeigerLU12 fatcat:dkmortaivbgizmdarx33fzvw7q
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