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Change detection based on features invariant to monotonic transforms and spatial constrained matching

Marco Tulio A. N. Rodrigues, Luciano O. Milen, Erickson R. Nascimento, William Robson Schwartz
<span title="">2014</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/rc5jnc4ldvhs3dswicq5wk3vsq" style="color: black;">2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)</a> </i> &nbsp;
Unlike most common approaches, which are pixel-based, we present an approach that combines super-pixel extraction, hierarchical clustering and segment matching.  ...  The experimental results show the effectiveness of the proposed approach comparing it a background subtraction technique, demonstrating the robustness of our algorithm to illumination variations, non-uniform  ...  The first step groups the segments generated by the super-pixel extraction using a binary hierarchical cluster tree.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2014.6854420">doi:10.1109/icassp.2014.6854420</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icassp/RodriguesMNS14.html">dblp:conf/icassp/RodriguesMNS14</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/coy7nb2mpnfhppoue7ergtlf4q">fatcat:coy7nb2mpnfhppoue7ergtlf4q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170811021411/http://homepages.dcc.ufmg.br/~erickson/publications/rodrigues_icassp2014.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f0/ad/f0ad89e2e2ad6cbe8160cce72a77ee1168b9db26.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icassp.2014.6854420"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Over-Segmentation Based Background Modeling and Foreground Detection with Shadow Removal by Using Hierarchical MRFs [chapter]

Te-Feng Su, Yi-Ling Chen, Shang-Hong Lai
<span title="">2011</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Next, each segment is treated as a node in a Markov Random Field and assigned a state of foreground, shadow and background, which is determined by using hierarchical belief propagation.  ...  A background model is learned by using Gaussian Mixture Models with color features of the segments to represent the time-varying background scene.  ...  Most traditional background modeling techniques are pixel-based, and they usually estimate the probability of the individual pixels belonging to background by using GMMs [1] or to label each pixel as  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-19318-7_42">doi:10.1007/978-3-642-19318-7_42</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ogljscicavb6hdxfg5mcg3eao4">fatcat:ogljscicavb6hdxfg5mcg3eao4</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20190220075030/http://pdfs.semanticscholar.org/20e6/b1f630e4318799fa91b15bb5fbc624257205.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/20/e6/20e6b1f630e4318799fa91b15bb5fbc624257205.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-19318-7_42"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Online Dominant and Anomalous Behavior Detection in Videos

Mehrsan Javan Roshtkhari, Martin D. Levine
<span title="">2013</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ilwxppn4d5hizekyd3ndvy2mii" style="color: black;">2013 IEEE Conference on Computer Vision and Pattern Recognition</a> </i> &nbsp;
In this paper, video events are learnt at each pixel without supervision using densely constructed spatio-temporal video volumes. Furthermore, the volumes are organized into large contextual graphs.  ...  These compositions are employed to construct a hierarchical codebook model for the dominant behaviors.  ...  detection and background subtraction.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2013.337">doi:10.1109/cvpr.2013.337</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/cvpr/RoshtkhariL13.html">dblp:conf/cvpr/RoshtkhariL13</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/buity54tm5h5npbhiskrep6e5q">fatcat:buity54tm5h5npbhiskrep6e5q</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20140401080402/http://www.cim.mcgill.ca:80/~javan/index_files/PapersAndPosters/Online%20Dominant%20and%20Anomalous%20Behavior%20Detection%20in%20Videos%20CVPR%202013.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/2d/cc/2dccec3c1a8a17883cece784e8f0fc0af413eb83.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/cvpr.2013.337"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Pedestrian detection for mobile bus surveillance

Wilson S. Leoputra, Svetha Venkatesh, Tele Tan
<span title="">2008</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/ivv5w2wonvgzdfvpd7q7w4wksm" style="color: black;">2008 10th International Conference on Control, Automation, Robotics and Vision</a> </i> &nbsp;
A kernel density estimation (KDE) method for colour and gradient foreground-background separation are then used to construct background model for each image cluster which is subsequently used to detect  ...  Finally, using a hierarchical template matching approach, pedestrians can be identified.  ...  Comparison between our approach and other approach We perform comparison on two different approaches for background subtraction: Stauffer-Grimson-based background subtraction [2] and the proposed KDE-based  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icarcv.2008.4795607">doi:10.1109/icarcv.2008.4795607</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icarcv/LeoputraVT08a.html">dblp:conf/icarcv/LeoputraVT08a</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gkfvmvor4vdwvfygsexav463rm">fatcat:gkfvmvor4vdwvfygsexav463rm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20171113043712/https://core.ac.uk/download/pdf/13997607.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/52/4c/524ce9be6eaa80cda392d3dd20a0a1eba530b4ef.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icarcv.2008.4795607"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Crowd density estimation based on optical flow and hierarchical clustering

Aravinda S. Rao, Jayavardhana Gubbi, Slaven Marusic, Paul Stanley, Marimuthu Palaniswami
<span title="">2013</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/3ezvnrqig5d5bmxdzmaqm4lk6e" style="color: black;">2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)</a> </i> &nbsp;
The Cophenetic correlation coefficient for the clusters highlighted the fact that our preprocessing and localizing of object movements form hierarchical clusters that are structured well with reasonable  ...  Furthermore, a hierarchical clustering is employed to cluster the objects based on Euclidean distance metric.  ...  Background subtraction considers a background model of the scene for a particular view and subtracts this model from incoming video frames to extract the foreground pixels.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icacci.2013.6637221">doi:10.1109/icacci.2013.6637221</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/icacci/RaoGMSP13.html">dblp:conf/icacci/RaoGMSP13</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7frdyipumrc3db5uszis52s2bm">fatcat:7frdyipumrc3db5uszis52s2bm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170215113826/http://people.eng.unimelb.edu.au:80/jgl/Papers/2013CrowdDensityICACCI.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/cf/6d/cf6d786144ad004f495660969903e34e17f503ea.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/icacci.2013.6637221"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

A COMPARISION OF VARIOUS EDGE DETECTION TECHNIQUES IN MOTION PICTURE FOR IDENTIFYING A SHARK FISH

Thiruvangadan
<span title="2013-11-01">2013</span> <i title="Science Publications"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wake4w3hqzd4ndiy2zowpciv64" style="color: black;">Journal of Computer Science</a> </i> &nbsp;
Structured hierarchical background procedure is proposed based on segmenting background images objects.  ...  It mainly divided the background images divided into several parts (regions) by the Support Vector Machine (SVM) followed by a structured hierarchical model is built with the region procedure and pixel  ...  A Hierarchical copy is developed from the segmented regions of background using Mean-shift algorithm. This Hierarchical model consists of two models, region model and pixel model.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3844/jcssp.2013.1427.1434">doi:10.3844/jcssp.2013.1427.1434</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/7etu2it625czzcmub7bh4dju54">fatcat:7etu2it625czzcmub7bh4dju54</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20160516043431/http://thescipub.com/PDF/jcssp.2013.1427.1434.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/76/35/7635637faf06c9c9b75f61f053b853200c45f513.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3844/jcssp.2013.1427.1434"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> Publisher / doi.org </button> </a>

Hierarchical Grid-Based People Tracking with Multi-camera Setup [chapter]

Lili Chen, Giorgio Panin, Alois Knoll
<span title="">2013</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jyopc6cf5ze5vipjlm4aztcffi" style="color: black;">Communications in Computer and Information Science</a> </i> &nbsp;
by clustering in pose-space.  ...  model, for a more precise localization.  ...  In Section 4, we provide the detailed detection procedure, including models, edge-based background subtraction, hierarchical grid evaluation as well as model-based contour matching and state-space clustering  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-32350-8_12">doi:10.1007/978-3-642-32350-8_12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2f47xqjlzjg2no37jhmzmubjsq">fatcat:2f47xqjlzjg2no37jhmzmubjsq</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20140422204607/http://www6.in.tum.de:80/Main/Publications/Chenlil2012a.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/22/26/22267d537cbaed08c2005c42f251bb6097aa1505.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-32350-8_12"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Probabilistic Model-Based Background Subtraction [chapter]

Volker Krüger, Jakob Anderson, Thomas Prehn
<span title="">2005</span> <i title="Springer Berlin Heidelberg"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a> </i> &nbsp;
Bayesian propagation over time is used for proper model selection and tracking during model-based background subtraction.  ...  Usually, background subtraction is approached as a pixelbased process, and the output is (a possibly thresholded) image where each pixel reflects, independent from its neighboring pixels, the likelihood  ...  They are able to learn a background as well as possible local image variations of it, thus generating a background model even of non-rigid background objects.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11499145_58">doi:10.1007/11499145_58</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/lhknwqoyi5ag3am4tmgiz2t6cu">fatcat:lhknwqoyi5ag3am4tmgiz2t6cu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20181030071700/https://link.springer.com/content/pdf/10.1007%2F11499145_58.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/99/4f/994f97c7177b2c40293075ed1eaa94f4c86a8552.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/11499145_58"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> springer.com </button> </a>

Computer Aided Detection of Suspicious Masses and Micro-Calcifications

M. Hanmandlu, D. Vineel, Vamsi Krishna Madasu, Shantaram Vasikarla
<span title="">2008</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q4htbe6iofd7zjlr6cgteixwfq" style="color: black;">Fifth International Conference on Information Technology: New Generations (itng 2008)</a> </i> &nbsp;
Segmentation of masses consists of three steps-background subtraction, fuzzy texture representation and entropic theresholding.  ...  Similarly micro-calcifications are also segmented in three stages -background subtraction, Laplacian of Gaussian filtering and contrast estimation followed by thresholding.  ...  Local Background Subtraction At first the mammogram is considered as a threedimensional plot with the third axis (z) corresponding to the intensity of each pixel.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/itng.2008.253">doi:10.1109/itng.2008.253</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/itng/HanmandluVMV08.html">dblp:conf/itng/HanmandluVMV08</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/rwirang4vvgspciegjyavnuvpi">fatcat:rwirang4vvgspciegjyavnuvpi</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170812220340/http://eprints.qut.edu.au/14419/1/14419a.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/70/fd/70fd6bd34714458f0147e7d4cd3deb9676a3a504.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/itng.2008.253"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Nonparametric Hierarchical Bayesian Models for Positive Data Clustering Based on Inverted Dirichlet-Based Distributions

Wentao Fan, Nizar bouguila
<span title="">2019</span> <i title="Institute of Electrical and Electronics Engineers (IEEE)"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/q7qi7j4ckfac7ehf3mjbso4hne" style="color: black;">IEEE Access</a> </i> &nbsp;
The efficacy and merits of the proposed approaches are examined using the synthetic data and a challenging real-life application that concerns video background subtraction.  ...  In this paper, we propose nonparametric hierarchical Bayesian models based on two inverted Dirichlet-based distributions and Pitman-Yor process for positive data features clustering.  ...  The proposed nonparametric hierarchical Bayesian models and the learning algorithms are validated using synthetic data and a real-life application namely video background subtraction.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2924651">doi:10.1109/access.2019.2924651</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/6at4tmwtlzeuxfrbhfher7uyui">fatcat:6at4tmwtlzeuxfrbhfher7uyui</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20210427093959/https://ieeexplore.ieee.org/ielx7/6287639/8600701/08744523.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/b9/74/b974819b6dfb060c0d3c4e7fe772c3c7bfc4a5cf.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/access.2019.2924651"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> ieee.com </button> </a>

Hierarchical Part-Template Matching for Human Detection and Segmentation

Zhe Lin, Larry S. Davis, David Doermann, Daniel DeMenthon
<span title="">2007</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/753trptklbb4nj6jquqadzwwdu" style="color: black;">2007 IEEE 11th International Conference on Computer Vision</a> </i> &nbsp;
We applied the approach to human detection and segmentation in crowded scenes with and without background subtraction.  ...  We describe a Bayesian approach to human detection and segmentation combining local part-based and global template-based schemes.  ...  Results with Background Subtraction We also evaluated our detector on two challenging surveillance video sequences using background subtraction.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2007.4408975">doi:10.1109/iccv.2007.4408975</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/iccv/LinDDD07.html">dblp:conf/iccv/LinDDD07</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kfauozqd4rggvkeelj6ugimcvm">fatcat:kfauozqd4rggvkeelj6ugimcvm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20120623071616/http://lampsrv02.umiacs.umd.edu/pubs/Papers/zhe-iccv07/zhe-iccv07.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/d5/a1/d5a17f1ea69f1c51cc3549d05f8f3a8e64d4d0bf.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/iccv.2007.4408975"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Chemical address tags of fluorescent bioimaging probes

Kerby Shedden, Gus R. Rosania
<span title="">2010</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/vlghmc36xnhadgvjbpyrvcjllq" style="color: black;">Cytometry Part A</a> </i> &nbsp;
Hierarchical clustering and paired imagecheminformatics analysis revealed key structure-property relationships amongst many building blocks of the fluorescent molecules.  ...  Here, using a large image dataset acquired with a high content screening instrument, machine vision and cheminformatics analysis have been applied to reveal chemical address tags.  ...  The background intensity of each of the images acquired corresponds to the median background pixel intensity as used in background subtraction.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1002/cyto.a.20847">doi:10.1002/cyto.a.20847</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/20104576">pmid:20104576</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC2907078/">pmcid:PMC2907078</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/2m3t667eqzfopgfk34qwvx7e4e">fatcat:2m3t667eqzfopgfk34qwvx7e4e</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170816103107/https://deepblue.lib.umich.edu/bitstream/handle/2027.42/71379/20847_ftp.pdf?sequence=1" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/77/8f/778f320fb898ea9b14713d118dfcaabf6ae475b8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1002/cyto.a.20847"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> wiley.com </button> </a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2907078" title="pubmed link"> <button class="ui compact blue labeled icon button serp-button"> <i class="file alternate outline icon"></i> pubmed.gov </button> </a>

Combining Background Subtraction and Convolutional Neural Network for Anomaly Detection in Pumping-Unit Surveillance

Tianming Yu, Jianhua Yang, Wei Lu
<span title="2019-05-29">2019</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/63zsvf7vxzfznojpqgfvpyk2lu" style="color: black;">Algorithms</a> </i> &nbsp;
In the proposed method, background subtraction was applied to first extract moving objects.  ...  Therefore, we combined background subtraction and a convolutional neural network to perform anomaly detection for pumping-unit surveillance.  ...  This clustering method uses data linkage criteria to repeatedly merge or split the data to build a hierarchy of clusters through a hierarchical architecture.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/a12060115">doi:10.3390/a12060115</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/cqlltzm26jf5vewsoo2p2ntbli">fatcat:cqlltzm26jf5vewsoo2p2ntbli</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200216065032/https://res.mdpi.com/d_attachment/algorithms/algorithms-12-00115/article_deploy/algorithms-12-00115.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/a1/c3/a1c38da890096b2137f76198baa28ef6ec3a23da.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/a12060115"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

A Multi-Scale Hierarchical Codebook Method for Human Action Recognition in Videos Using a Single Example

Mehrsan Javan Roshtkhari, Martin D. Levine
<span title="">2012</span> <i title="IEEE"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/o4jogpoqo5hlfpyg2izplwcaim" style="color: black;">2012 Ninth Conference on Computer and Robot Vision</a> </i> &nbsp;
This paper presents a novel action matching method based on a hierarchical codebook of local spatiotemporal video volumes (STVs).  ...  It is based on the bag of video words (BOV) representation and does not require prior knowledge about actions, background subtraction, motion estimation or tracking.  ...  It uses a hierarchical approach, in which a two-level clustering method is employed. At the first level, all similar video volumes are clustered.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/crv.2012.32">doi:10.1109/crv.2012.32</a> <a target="_blank" rel="external noopener" href="https://dblp.org/rec/conf/crv/RoshtkhariL12.html">dblp:conf/crv/RoshtkhariL12</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/woqfp4exlbbytbpkydgsjfni5i">fatcat:woqfp4exlbbytbpkydgsjfni5i</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170811092350/http://www.cim.mcgill.ca/%7Ejavan/index_files/PapersAndPosters/A%20Multi-Scale%20Hierarchical%20Codebook%20Method%20for%20Human%20Action%20Recognition%20in%20Videos%20Using%20a%20Single%20Example.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/e1/61/e1618270d620de5ef0e5a0e63f35d98f7758392e.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/crv.2012.32"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Multi-Layer Multi-Feature Background Subtraction Using Codebook Model Framework

Yun-Tao Zhang, Jong-Yeop Bae, Whoi-Yul Kim
<span title="2015-11-02">2015</span> <i title="Zenodo"> Zenodo </i> &nbsp;
modeling and subtraction in video analysis has been widely used as an effective method for moving objects detection in many computer vision applications.  ...  Experimental results on several popular background subtraction datasets demonstrate very competitive performance compared to previous models.  ...  In addition to this, local binary pattern (LBP) has been used to model the background with a group of weighted adaptive LBP histograms in order to obtain the background statistics of each image block  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.1110686">doi:10.5281/zenodo.1110686</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/uzhyok25kffdlpngai3atghkcm">fatcat:uzhyok25kffdlpngai3atghkcm</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20200216082148/https://zenodo.org/record/1110686/files/10003227.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/fe/f2/fef2a0b5c56be12f9891800c3bd18a3de5cfb064.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.5281/zenodo.1110686"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> zenodo.org </button> </a>
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