{"id":321,"date":"2024-09-20T04:11:43","date_gmt":"2024-09-20T02:11:43","guid":{"rendered":"https:\/\/ics.science.upjs.sk\/ano\/?page_id=321"},"modified":"2025-12-22T13:37:47","modified_gmt":"2025-12-22T12:37:47","slug":"prednasky","status":"publish","type":"page","link":"https:\/\/ics.science.upjs.sk\/ano\/prednasky\/","title":{"rendered":"Predn\u00e1\u0161ky"},"content":{"rendered":"<ul>\n<li>16.09.2025: bez predn\u00e1\u0161ky<\/li>\n<li><strong>23.09.2025:<\/strong> 1. \u00davod do po\u010d\u00edta\u010dov\u00e9ho videnia<\/li>\n<li><strong>30.09.2025: <\/strong>2. Farebn\u00fd, \u0161edot\u00f3nov\u00fd, bin\u00e1rny obraz. Prahovanie, histogram, vyhladzovanie histogramu. Matematick\u00e1 morfol\u00f3gia.<\/li>\n<li><strong>07.10.2025:<\/strong> 3. \u0160um, odstra\u0148ovanie \u0161umu. Filtrovanie, konvol\u00facia. Indoor lokaliz\u00e1cia.<\/li>\n<li><strong>14.10.2025:<\/strong> 4. Filtrovanie vo frekven\u010dnej oblasti, Fourierov\u00e1 tranform\u00e1cia, konvolu\u010dn\u00e1 veta, s\u00ednusoida, vzorkovanie, aliasing. Met\u00f3da najmen\u0161\u00edch \u0161tvorcov, RANSAC. Hough transform\u00e1cia na n\u00e1jdenie \u010diar a kruhov.<\/li>\n<li><strong>21.10.2025:<\/strong> 5. Detekcia hr\u00e1n, gradient, laplacian, Cannyho hranov\u00fd detektor, detekcia rohov.<\/li>\n<li><strong>28.10.2025:<\/strong> 6. Segment\u00e1cia obrazu. Klastrovanie (k\u00ad-\u2060means, meanshift). Grabcut. Met\u00f3da akt\u00edvnych kont\u00far. Text\u00fary.<\/li>\n<li><strong>04.11.2025:<\/strong> 7. Pr\u00edznaky. Blob detekcia. SIFT detektor a deskriptor. Geometrick\u00e9 transform\u00e1cie.<\/li>\n<li>11.11.2025: bez predn\u00e1\u0161ky &#8211; bude cvi\u010denie<\/li>\n<li>18.11.2025: predn\u00e1\u0161ka zru\u0161en\u00e1<\/li>\n<li><strong>25.11.2025:<\/strong> 8. Rozpozn\u00e1vanie. Strojov\u00e9 u\u010denie a neur\u00f3nov\u00e9 siete v oblasti po\u010d\u00edta\u010dov\u00e9ho videnia. Predspracovanie obr\u00e1zkov, image whitening, augment\u00e1cia d\u00e1t. Detekcia tv\u00e1re, Haar features.<\/li>\n<li><strong>02.12.2025:<\/strong> 9. Sledovanie objektu na sekvenci\u00ed obr\u00e1zkov, mixture of gaussians, template matching, tracking.<\/li>\n<li><strong>09.12.2025:<\/strong> 10. Vznik obrazu &#8211; dierkov\u00e1 kamera. Projekcia z 3D do 2D, vonkaj\u0161ia a vn\u00fatorn\u00e1 matica, kalibr\u00e1cia kamery, epipol\u00e1rna geometria, h\u013abka obrazu.<\/li>\n<li>16.12.2025: bez predn\u00e1\u0161ky<\/li>\n<\/ul>\n<hr \/>\n<h3>1. \u00davod do po\u010d\u00edta\u010dov\u00e9ho videnia<\/h3>\n<ul>\n<li><a href=\"http:\/\/karpathy.github.io\/2012\/10\/22\/state-of-computer-vision\/\">Obama na v\u00e1he<\/a>\u00a0\u2013 blog \u010dl\u00e1nok o stave AI pri poh\u013eade na fotku<\/li>\n<li><a href=\"https:\/\/cloud.google.com\/vision\">Google Cloud Vision<\/a>\u00a0\u2013 d\u00e1 sa vysk\u00fa\u0161a\u0165 rozpozn\u00e1vanie obr\u00e1zkov<\/li>\n<\/ul>\n<h3>2. Farebn\u00fd, \u0161edot\u00f3nov\u00fd, bin\u00e1rny obraz. Prahovanie, histogram, vyhladzovanie histogramu. Matematick\u00e1 morfol\u00f3gia.<\/h3>\n<p><em>Tento obsah je pokryt\u00fd v skript\u00e1ch. Vyhladzovaniu histogramu sme sa venovali na cvi\u010deniach.<\/em><\/p>\n<ul>\n<li><a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2025\/09\/02-binarne-obrazy.pptx.pdf\">slajdy<\/a><\/li>\n<li><a href=\"https:\/\/www.redblobgames.com\/grids\/hexagons\/\">\u0160es\u0165uholn\u00edky<\/a><\/li>\n<li><a href=\"https:\/\/playgameoflife.com\/\">Game of life<\/a><\/li>\n<li><a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2025\/09\/nFtqv8e.jpg\">obr\u00e1zok<\/a> + <a href=\"https:\/\/www.gimp.org\/\">GIMP<\/a><\/li>\n<\/ul>\n<h3>3. \u0160um, odstra\u0148ovanie \u0161umu. Filtrovanie, konvol\u00facia.<\/h3>\n<p><em>Tento obsah nie je v skript\u00e1ch. Slajdy s\u00fa len pomocn\u00e9 k predn\u00e1\u0161ke. Indoor lokaliz\u00e1cia je bonusov\u00fd obsah. Pre \u0161um a konvol\u00faciu odpor\u00fa\u010dam pozrie\u0165 na zoznam literat\u00fary.<\/em><\/p>\n<ul>\n<li><a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2022\/10\/03-filtrovanie.pdf\">slajdy<\/a><\/li>\n<li><a href=\"https:\/\/www.cambridgeincolour.com\/tutorials\/gamma-correction.htm#:~:text=Gamma%20correction%20is%20sometimes%20specified,1%2F1.5%20%3D%201.0).\">Gamma korekcia<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/Convolution\">konvol\u00facia<\/a>\u00a0\u2013 vizualiz\u00e1cia na wikip\u00e9dii<\/li>\n<li><a href=\"https:\/\/ics.upjs.sk\/~opiela\/iot\/uvod-do-iot\/\">Indoor lokaliz\u00e1cia<\/a> (2021) + <a href=\"https:\/\/ics.science.upjs.sk\/indora\/\">aktu\u00e1lny v\u00fdskum<\/a><\/li>\n<\/ul>\n<h3>4. Filtrovanie vo frekven\u010dnej oblasti. Hough transform\u00e1cia.<\/h3>\n<p><em>Obsah nem\u00e1m pokryt\u00fd v skript\u00e1ch. Ide o viacero osobitn\u00fdch t\u00e9m.\u00a0<\/em><\/p>\n<ul>\n<li><a href=\"https:\/\/www.geogebra.org\/m\/wUanseCs\">Geogebra<\/a> &#8211; square wave dekompoz\u00edcia pomocou fourierovej transform\u00e1cie<\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/File:Fourier_transform_time_and_frequency_domains.gif\">Fourierov\u00e1 transform\u00e1cia<\/a> &#8211; anim\u00e1cia + <a href=\"https:\/\/upload.wikimedia.org\/wikipedia\/commons\/6\/6b\/SquareWaveFourierArrows.gif\">anim\u00e1cia<\/a> pomocou \u0161\u00edpok<\/li>\n<li>samplovanie &#8211; <a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2024\/10\/transformacie-slajd1.png\">slajd1<\/a> <a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2024\/10\/transformacie-slajd2.png\">slajd2<\/a> <a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2024\/10\/transformacie-slajd3.png\">slajd3<\/a><\/li>\n<li><a href=\"https:\/\/www.youtube.com\/watch?v=ebfi7qOFLuo\">Hough transform\u00e1cia<\/a> &#8211; youtube video, demo<\/li>\n<\/ul>\n<h3>5. Detekcia hr\u00e1n, gradient, laplacian, Cannyho hranov\u00fd detektor, detekcia rohov.<\/h3>\n<p><em>\u00davod o hran\u00e1ch a gradient je pokryt\u00fd v skript\u00e1ch. Materi\u00e1ly k tejto t\u00e9me s\u00fa najlep\u0161ie vo <a href=\"https:\/\/cave.cs.columbia.edu\/Statics\/monographs\/Edge%20Detection%20FPCV-2-1.pdf\">First Principle<\/a> (viac v zozname literat\u00fary).<\/em><\/p>\n<ul>\n<li><a href=\"https:\/\/opencv24-python-tutorials.readthedocs.io\/en\/latest\/py_tutorials\/py_imgproc\/py_canny\/py_canny.html\">Canny edge detection<\/a>\u00a0\u2013 opencv<\/li>\n<\/ul>\n<h3>6. Segment\u00e1cia obrazu. Klastrovanie (k\u00ad-\u2060means, meanshift). Grabcut. Met\u00f3da akt\u00edvnych kont\u00far. Text\u00fary.<\/h3>\n<p><em>V skript\u00e1ch je GrabCut. Ostatn\u00e9 s\u00fa pokryt\u00e9 vo vide\u00e1ch z kurzu First Principles. Text\u00fary nie s\u00fa pre n\u00e1s podstatn\u00e1 t\u00e9ma, spomen\u00fa sa len okrajovo, aby sme videli niektor\u00e9 v\u00fdzvy a rie\u0161enia.<\/em><\/p>\n<ul>\n<li><a href=\"https:\/\/cave.cs.columbia.edu\/Statics\/monographs\/Image%20Segmentation%20FPCV-5-2.pdf\">segment\u00e1cia<\/a> &#8211; u\u010debn\u00fd text k first principles<\/li>\n<li><a href=\"https:\/\/cave.cs.columbia.edu\/Statics\/monographs\/Boundary%20Detection%20FPCV-2-2.pdf\">akt\u00edvne kont\u00fary<\/a> &#8211; u\u010debn\u00fd text k first principles<\/li>\n<li><a href=\"https:\/\/opencv24-python-tutorials.readthedocs.io\/en\/latest\/py_tutorials\/py_imgproc\/py_contours\/py_contours_begin\/py_contours_begin.html\">kont\u00fary<\/a> opencv<\/li>\n<li>text\u00fary &#8211; <a href=\"https:\/\/www.cs.ubc.ca\/~lsigal\/425_2018W2\/Lecture10b.pdf\">slajdy synt\u00e9za<\/a>, <a href=\"https:\/\/courses.cs.washington.edu\/courses\/cse576\/10sp\/notes\/Texture_white.pdf\">slajdy anal\u00fdza<\/a><\/li>\n<\/ul>\n<h3>7. Pr\u00edznaky. Blob detekcia. SIFT detektor a deskriptor. Geometrick\u00e9 transform\u00e1cie.<\/h3>\n<p><em>Nem\u00e1m pokryt\u00e9 v skript\u00e1ch. I\u0161iel som pod\u013ea First principles.<\/em><\/p>\n<ul>\n<li><a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2022\/11\/07-features.pdf\">prezent\u00e1cia<\/a>\u00a0\u2013 features<\/li>\n<li><a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2024\/11\/geometricketransformacie.pdf\">prezent\u00e1cia<\/a>\u00a0\u2013 geometrick\u00e9 transform\u00e1cie<\/li>\n<li><a href=\"https:\/\/wordsandbuttons.online\/interactive_guide_to_homogeneous_coordinates.html\">interakt\u00edvne transform\u00e1cie<\/a><\/li>\n<li><a href=\"https:\/\/en.wikipedia.org\/wiki\/File:Affine_transformations.ogv\">afinn\u00e1 transform\u00e1cia<\/a><\/li>\n<li><a href=\"https:\/\/opencv24-python-tutorials.readthedocs.io\/en\/latest\/py_tutorials\/py_feature2d\/py_sift_intro\/py_sift_intro.html#sift-intro\">sift<\/a>\u00a0\u2013 opencv<\/li>\n<\/ul>\n<h3>8. Rozpozn\u00e1vanie. Strojov\u00e9 u\u010denie a neur\u00f3nov\u00e9 siete v oblasti po\u010d\u00edta\u010dov\u00e9ho videnia. Predspracovanie obr\u00e1zkov, image whitening, augment\u00e1cia d\u00e1t. Detekcia tv\u00e1re, Haar features<\/h3>\n<p><em>Z viacer\u00fdch zdrojov. Viac detailov v zozname literat\u00fary. Preh\u013ead o datasetoch nem\u00e1m v materi\u00e1loch &#8211; ale nie je s\u00fa\u010das\u0165ou sk\u00fa\u0161ky.\u00a0<\/em><\/p>\n<div class=\"site-section-wrapper site-section-wrapper-main\">\n<div id=\"site-page-columns\">\n<div id=\"site-column-main\" class=\"site-column site-column-main\">\n<div class=\"site-column-main-wrapper\">\n<div class=\"entry-content\">\n<ul>\n<li><a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2023\/11\/Screenshot-from-2023-11-28-11-28-56.png\">ML<\/a><\/li>\n<li><a href=\"https:\/\/www.cs.cornell.edu\/courses\/cs5670\/2022sp\/lectures\/lec19_intro_recognition_for_web.pdf\">recognition<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/hadrienj\/Preprocessing-for-deep-learning\/blob\/master\/Preprocessing-for-deep-learning.ipynb\">image whitening<\/a><\/li>\n<li><a href=\"https:\/\/quickdraw.withgoogle.com\/#\">quick draw<\/a><\/li>\n<li><a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2023\/11\/obhajoba_BP.pdf\">image modification NN<\/a><\/li>\n<li><a href=\"https:\/\/ai.google.dev\/edge\/mediapipe\/solutions\/guide\">mediapipe<\/a><\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<h3>9. Tracking<\/h3>\n<p><em>Single object tracking je v skript\u00e1ch. Multi object tracking je v prezent\u00e1cii.<\/em><\/p>\n<ul>\n<li><a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2025\/12\/09-tracking.pdf\">SLAJDY<\/a><\/li>\n<li>kamery\u00a0<a href=\"https:\/\/kukaj.se\/\">Pre\u0161ov<\/a>,\u00a0<a href=\"http:\/\/dopravanazivo.tvkosice.sk\/\">Ko\u0161ice<\/a><\/li>\n<li><a href=\"http:\/\/www.ai.mit.edu\/projects\/vsam\/Publications\/stauffer_cvpr98_track.pdf\">Gaussian mixture model<\/a><\/li>\n<li><a href=\"https:\/\/broutonlab.com\/blog\/opencv-object-tracking\">Object tracking algoritmy<\/a><\/li>\n<li><a href=\"https:\/\/www.thinkautonomous.ai\/blog\/computer-vision-for-tracking\/\">Computer vision for tracking<\/a><\/li>\n<li><a href=\"https:\/\/www.thinkautonomous.ai\/blog\/hungarian-algorithm\/\">Hungarian algorithm<\/a><\/li>\n<li><a href=\"https:\/\/www.votchallenge.net\/\">VOT challenge<\/a><\/li>\n<li><a href=\"https:\/\/motchallenge.net\/\">MOT challenge<\/a><\/li>\n<li><a href=\"https:\/\/docs.ultralytics.com\/modes\/track\/\">YOLO ultralytics tracking<\/a><\/li>\n<li><a href=\"https:\/\/web.archive.org\/web\/20161021234724id_\/http:\/\/www.dynamicdetection.com:80\/papers\/Bewley_SORT_cameraready.pdf\">SORT \u010dl\u00e1nok<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/pdf\/1703.07402\/1000\">DeepSORT \u010dl\u00e1nok<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/NirAharon\/BoT-SORT\">Bot-SORT<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/FoundationVision\/ByteTrack\">ByteTrack<\/a><\/li>\n<li><a href=\"https:\/\/miguel-mendez-ai.com\/2024\/08\/25\/mot-tracking-metrics\">metriky<\/a><\/li>\n<\/ul>\n<div id=\"site-footer-credit\">\n<div class=\"site-section-wrapper site-section-wrapper-footer-credit\"><\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>16.09.2025: bez predn\u00e1\u0161ky 23.09.2025: 1. \u00davod do po\u010d\u00edta\u010dov\u00e9ho videnia 30.09.2025: 2. Farebn\u00fd, \u0161edot\u00f3nov\u00fd, bin\u00e1rny obraz. Prahovanie, histogram, vyhladzovanie histogramu. Matematick\u00e1 morfol\u00f3gia. 07.10.2025: 3. \u0160um, odstra\u0148ovanie \u0161umu. Filtrovanie, konvol\u00facia. Indoor lokaliz\u00e1cia.&hellip;<\/p>\n","protected":false},"author":22,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-321","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/pages\/321","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/users\/22"}],"replies":[{"embeddable":true,"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/comments?post=321"}],"version-history":[{"count":39,"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/pages\/321\/revisions"}],"predecessor-version":[{"id":496,"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/pages\/321\/revisions\/496"}],"wp:attachment":[{"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/media?parent=321"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}