{"id":63,"date":"2022-09-26T11:15:11","date_gmt":"2022-09-26T09:15:11","guid":{"rendered":"https:\/\/ics.science.upjs.sk\/ano\/?page_id=63"},"modified":"2025-12-19T20:32:18","modified_gmt":"2025-12-19T19:32:18","slug":"literatura","status":"publish","type":"page","link":"https:\/\/ics.science.upjs.sk\/ano\/literatura\/","title":{"rendered":"Literat\u00fara"},"content":{"rendered":"<ul>\n<li><strong>[SZELISKI]<\/strong> Richard Szeliski <a href=\"https:\/\/szeliski.org\/Book\/\">Computer Vision: Algorithms and Applications, 2nd ed.<\/a> &#8211; kniha je vo\u013ene dostupn\u00e1 po zadan\u00ed emailu.<\/li>\n<li><strong>[NAYAR]<\/strong> <a href=\"https:\/\/fpcv.cs.columbia.edu\/\">First principles of computer vision<\/a> &#8211; online kurz, vide\u00e1 vo\u013ene dostupn\u00e9 + lecture notes (monographs)<\/li>\n<li><strong>[SONKA]<\/strong> \u0160ONKA, MIlan, HLAV\u00c1\u010c, V\u00e1clav a Roger BOYLE:<a href=\"https:\/\/www.cl72.org\/090imagePLib\/books\/sonka,hlavac,boyle-imageProc.pdf\"> Image Processing, Analysis, and Machine Vision<\/a>. &#8211; 4. ed\u00edcia<\/li>\n<li><strong>[\u0160IKUDOV\u00c1] <\/strong>E. \u0160ikudov\u00e1, Z. \u010cernekov\u00e1, W. Bene\u0161ov\u00e1, Z. Haladov\u00e1, and J. Ku\u010derov\u00e1, <a href=\"https:\/\/is.stuba.sk\/vv\/pub_priloha.pl?id=291415\">Po\u010d\u00edta\u010dov\u00e9 videnie<\/a> Detekcia a rozpozn\u00e1vanie objektov. Praha: Wikina Praha, 2013, p. 397.<\/li>\n<li><strong>[FORSYTH]<\/strong> Forsyth, D. A., &amp; Ponce, J. (2002).<a href=\"https:\/\/preterhuman.net\/docs\/images\/6\/6e\/Computer_Vision_A_Modern_Approach_-_Forsyth_%2C_Ponce.pdf\">\u00a0<i>Computer vision: a modern approach<\/i>.<\/a><\/li>\n<li><a href=\"https:\/\/opencv24-python-tutorials.readthedocs.io\/en\/latest\/py_tutorials\/py_tutorials.html\">OpenCV python tutorials<\/a><\/li>\n<\/ul>\n<h2>T\u00e9my:<\/h2>\n<ul>\n<li><strong>\u00davod do Computer Vision<\/strong>\u00a0\u2013 [SZELISKI] chapter 1 \u2013 Introduction, [SZELISKI] Conclusion, [SONKA] chapter 1 \u2013 introduction<\/li>\n<li><strong>Thresholding, bin\u00e1rne obrazy &#8211; <\/strong>[SONKA] chapter 6.1<\/li>\n<li><strong>Metrika, vzdialenos\u0165, susedstvo<\/strong>\u00a0\u2013 [\u0160IKUDOV\u00c1] Morfologick\u00e9 oper\u00e1cie \u2013 4.2. Z\u00e1kladn\u00e9 pojmy a defin\u00edcie<\/li>\n<li><strong>Matematick\u00e1 morfol\u00f3gia<\/strong>\u00a0\u2013 [SONKA] chapter 13 \u2013 Mathematical morphology<\/li>\n<li><strong>Transform\u00e1cia pixelov, bodov\u00e9 oper\u00e1tory, vyhladzovanie histogramov<\/strong> \u2013 [SZELISKI] chapter 3.1.<\/li>\n<li><strong>\u0160um <\/strong>&#8211; [SONKA] 2.3.6<\/li>\n<li><strong>Line\u00e1rne a neline\u00e1rne filtrovanie, konvol\u00facia<\/strong> \u2013 [NAYAR] Imaging -&gt; Image Processing I., [SZELISKI] &#8211; 3.2., 3.3.<\/li>\n<li><strong>Transform\u00e1cie<\/strong> (vzorkovanie, aliasing, frekven\u010dn\u00e1 dom\u00e9na (s\u00ednusoida, square wave), Fourierov\u00e1 transform\u00e1cia, Konvolu\u010dn\u00e1 veta) &#8211; [NAYAR] Imaging -&gt; Image Processing II.<\/li>\n<li><strong>Geometrick\u00e9 transform\u00e1cie<\/strong> &#8211; [SZELISKI] 3.6, [NAYAR] Features -&gt; Image Stitching<\/li>\n<li><strong>Detekcia hr\u00e1n<\/strong> <strong>a rohov<\/strong> (Gradient, Laplacian, Cannyho detektor, Harris Corner detection) &#8211; [NAYAR] Features -&gt; Edge Detection<\/li>\n<li><strong>Detekcie<\/strong> (fitting lines, akt\u00edvne kont\u00fary, Hough transform\u00e1cia na \u010diary a kruhy) &#8211; [NAYAR] Features -&gt; Boundary detection<\/li>\n<li><strong>Template matching<\/strong> &#8211; [SONKA] 6.4 Matching<\/li>\n<li><strong>Segment\u00e1cia<\/strong> (k-means,\u00a0mean shift, GrabCut) &#8211; [NAYAR] Perception -&gt; Image Segmentation<\/li>\n<li><strong>Pr\u00edznaky<\/strong> &#8211; [SZELISKI] 7.1<\/li>\n<li><strong>SIFT, deskriptor<\/strong> &#8211; [NAYAR] Features -&gt; SIFT Detector<\/li>\n<li><strong>Sp\u00e1janie obrazov<\/strong> &#8211; [NAYAR] Features -&gt; Image Stitching<\/li>\n<li><strong>Detekcia tv\u00e1re<\/strong> (Haar features, Integral image, klasifik\u00e1cia, SVM) &#8211; [NAYAR] Features -&gt; Face Detection<\/li>\n<li><strong>Rozpozn\u00e1vanie, deep learning, CNN<\/strong> &#8211; [SZELISKI] 5<\/li>\n<li><strong>Image whitening<\/strong> &#8211; <a href=\"https:\/\/www.kdnuggets.com\/2018\/10\/preprocessing-deep-learning-covariance-matrix-image-whitening.html\">J. Hadrien<\/a><\/li>\n<li><strong>Text\u00fary<\/strong> (anal\u00fdza a synt\u00e9za) &#8211; [SZELISKI] 10.5<\/li>\n<li><strong>Tracking<\/strong> (rozdiel obr\u00e1zkov, gaussian mixture model, template matching, feature detection) &#8211; [NAYAR] Perception -&gt; Object Tracking<\/li>\n<li><strong>Multi object tracking <\/strong>&#8211; r\u00f4zne zdroje (vi\u010f <a href=\"https:\/\/ics.science.upjs.sk\/ano\/wp-content\/uploads\/sites\/17\/2025\/12\/09-tracking.pdf\">slajdy<\/a>)<\/li>\n<li><strong>Vznik obrazu<\/strong> &#8211; [NAYAR] Imaging -&gt; Image Formation<\/li>\n<li><strong>3D &#8211; Vn\u00fatorn\u00e1 a vonkaj\u0161ia matica, kalibr\u00e1cia kamery<\/strong> &#8211; [NAYAR] Reconstruction II. -&gt; Camera Calibration resp.\u00a0(<a href=\"https:\/\/medium.com\/data-science\/image-formation-and-pinhole-model-of-the-camera-53872ee4ee92\">1<\/a>, <a href=\"https:\/\/medium.com\/data-science\/camera-extrinsic-matrix-with-example-in-python-cfe80acab8dd\">2<\/a>, <a href=\"https:\/\/medium.com\/data-science\/camera-intrinsic-matrix-with-example-in-python-d79bf2478c12\">3<\/a>)<\/li>\n<li><strong>3D &#8211; epipol\u00e1rna geometria<\/strong> &#8211; [NAYAR] Reconstruction II. -&gt; Uncalibrated Stereo<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"<p>[SZELISKI] Richard Szeliski Computer Vision: Algorithms and Applications, 2nd ed. &#8211; kniha je vo\u013ene dostupn\u00e1 po zadan\u00ed emailu. [NAYAR] First principles of computer vision &#8211; online kurz, vide\u00e1 vo\u013ene dostupn\u00e9&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-63","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/pages\/63","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=63"}],"version-history":[{"count":21,"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/pages\/63\/revisions"}],"predecessor-version":[{"id":493,"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/pages\/63\/revisions\/493"}],"wp:attachment":[{"href":"https:\/\/ics.science.upjs.sk\/ano\/wp-json\/wp\/v2\/media?parent=63"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}