Diferencia entre revisiones de «Materiales para el curso de Percepción Artificial en el master de la Facultad de Informática UPV/EHU»

De Grupo de Inteligencia Computacional (GIC)
 
(No se muestran 53 ediciones intermedias de 3 usuarios)
Línea 6: Línea 6:


* [http://www.cs.uwaterloo.ca/~mannr/cs886-w10/ Percepción  e inferencia bayesiana, curso en la Univ. Waterloo]
* [http://www.cs.uwaterloo.ca/~mannr/cs886-w10/ Percepción  e inferencia bayesiana, curso en la Univ. Waterloo]
* visual recognition, tutorial AAAI 08 [http://www.vision.ee.ethz.ch/~bleibe/teaching/tutorial-aaai08/]


=Refencias de revistas y presentaciones=
=Refencias de revistas y presentaciones=
Línea 12: Línea 14:
* [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4308348 percepcion artificial en arrays adaptativos, 1980]
* [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=4308348 percepcion artificial en arrays adaptativos, 1980]
* [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=485770 sensores naturales "no convencionales", los extraños sensores de otras especies....]
* [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=485770 sensores naturales "no convencionales", los extraños sensores de otras especies....]
* the visual system by Jeanny Herault [http://www.lis.inpg.fr/pages_perso/herault/Documents_files/Lectures/pres_HTML/2_VisSyst/sld001.htm] and some visual illusions [http://www.lis.inpg.fr/pages_perso/herault/Documents_files/Lectures/pres_HTML/0_Visual_Illusions/0-index.htm]
* tutorial on random forests [http://research.microsoft.com/en-us/groups/vision/decisionforests.aspx]
 
* A Bayesian framework for active artificial perception [http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6310070]
== face detection and recognition ==
== face detection and recognition ==
*[http://www.face-rec.org/ face recognition homepage]
*[http://www.face-rec.org/ face recognition homepage]
Línea 19: Línea 21:
* biometrics [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=11&ved=0CB4QFjAAOAo&url=http%3A%2F%2Fclassweb.gmu.edu%2Fjgifford%2FBIOMETRICS.ppt&ei=MWinTpqxGYmZ8QOmg7mjDw&usg=AFQjCNFAtvmdGj_ErA5TRAcbnQqG4tvQIA&cad=rja]
* biometrics [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=11&ved=0CB4QFjAAOAo&url=http%3A%2F%2Fclassweb.gmu.edu%2Fjgifford%2FBIOMETRICS.ppt&ei=MWinTpqxGYmZ8QOmg7mjDw&usg=AFQjCNFAtvmdGj_ErA5TRAcbnQqG4tvQIA&cad=rja]
* detecting faces [http://courses.cs.tamu.edu/rgutier/cpsc689_s07/yang2002faceDetectionSurveySLIDES.pdf], recent advances (2004) [http://vision.ai.uiuc.edu/mhyang/papers/icpr04_tutorial.pdf], adaboost for face detection [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=3&ved=0CDkQFjAC&url=http%3A%2F%2Fwww.cs.huji.ac.il%2Fcourse%2F2004%2Flearns%2FFaceDetection.ppt&ei=3WOnTpeCAdPB8QPbt43UDw&usg=AFQjCNHKmwHtDRRR-VsARUAOMOxbASE1mQ], face detection Viola [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=2&ved=0CC8QFjAB&url=http%3A%2F%2Fwww.cs.unc.edu%2F~lazebnik%2Fspring09%2Flec23_face_detection.ppt&ei=3WOnTpeCAdPB8QPbt43UDw&usg=AFQjCNHJ5q_jRt8YqXs5OaPQ-YD6YqqvRg], viola-jones [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=12&ved=0CCgQFjABOAo&url=http%3A%2F%2Fwww.ics.uci.edu%2F~smyth%2Fcourses%2Fcs175%2Fslides12_viola_jones_face_detection.ppt&ei=MWinTpqxGYmZ8QOmg7mjDw&usg=AFQjCNHpYTK_m9tRWibEEceKRHRsk-xmuw], pose and light invariant [http://www.biometrics.org/bc2004/Presentations/Conference/2%20Tuesday%20September%2021/Tue_Ballroom%20A/5%20TSWG/Ansari.pdf]
* detecting faces [http://courses.cs.tamu.edu/rgutier/cpsc689_s07/yang2002faceDetectionSurveySLIDES.pdf], recent advances (2004) [http://vision.ai.uiuc.edu/mhyang/papers/icpr04_tutorial.pdf], adaboost for face detection [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=3&ved=0CDkQFjAC&url=http%3A%2F%2Fwww.cs.huji.ac.il%2Fcourse%2F2004%2Flearns%2FFaceDetection.ppt&ei=3WOnTpeCAdPB8QPbt43UDw&usg=AFQjCNHKmwHtDRRR-VsARUAOMOxbASE1mQ], face detection Viola [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=2&ved=0CC8QFjAB&url=http%3A%2F%2Fwww.cs.unc.edu%2F~lazebnik%2Fspring09%2Flec23_face_detection.ppt&ei=3WOnTpeCAdPB8QPbt43UDw&usg=AFQjCNHJ5q_jRt8YqXs5OaPQ-YD6YqqvRg], viola-jones [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=12&ved=0CCgQFjABOAo&url=http%3A%2F%2Fwww.ics.uci.edu%2F~smyth%2Fcourses%2Fcs175%2Fslides12_viola_jones_face_detection.ppt&ei=MWinTpqxGYmZ8QOmg7mjDw&usg=AFQjCNHpYTK_m9tRWibEEceKRHRsk-xmuw], pose and light invariant [http://www.biometrics.org/bc2004/Presentations/Conference/2%20Tuesday%20September%2021/Tue_Ballroom%20A/5%20TSWG/Ansari.pdf]
* 3D detection applied to faces and cars [http://www.cse.unr.edu/~bebis/CS679/PaperPresentations/schneiderman00.ppt]
* face detection and recognition [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=6&ved=0CFoQFjAF&url=http%3A%2F%2Fwww.cs.columbia.edu%2F~belhumeur%2Fcourses%2Fbiometrics%2F2010%2FFace%2520Detection%2520and%2520Recognition.ppt&ei=2GGnTvz7J4Ol8QOx89TeDw&usg=AFQjCNH-O5eCejESa1GaUK4_tPiBFZtmFQ], [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=1&ved=0CCUQFjAA&url=http%3A%2F%2Fwww.ee.pdx.edu%2F~mperkows%2FCLASS_479%2FBiometrics%2FFaceRecognition%2FIntroFaceDetectRecognition.ppt&ei=3WOnTpeCAdPB8QPbt43UDw&usg=AFQjCNHls-pb_d-lhmFoun8AXl19YyPhPg]
* face detection and recognition [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=6&ved=0CFoQFjAF&url=http%3A%2F%2Fwww.cs.columbia.edu%2F~belhumeur%2Fcourses%2Fbiometrics%2F2010%2FFace%2520Detection%2520and%2520Recognition.ppt&ei=2GGnTvz7J4Ol8QOx89TeDw&usg=AFQjCNH-O5eCejESa1GaUK4_tPiBFZtmFQ], [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=1&ved=0CCUQFjAA&url=http%3A%2F%2Fwww.ee.pdx.edu%2F~mperkows%2FCLASS_479%2FBiometrics%2FFaceRecognition%2FIntroFaceDetectRecognition.ppt&ei=3WOnTpeCAdPB8QPbt43UDw&usg=AFQjCNHls-pb_d-lhmFoun8AXl19YyPhPg]
* face recognition [http://www.umiacs.umd.edu/~joseph/face-recognition.pdf], [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=7&ved=0CGAQFjAG&url=http%3A%2F%2Fwww.scourge.fr%2Fmathdesc%2Fdocuments%2Ffacerecog%2Ffinal.ppt&ei=2GGnTvz7J4Ol8QOx89TeDw&usg=AFQjCNH7rmVmML_FYbrBMFEPtI9JSBwS8A], PCA vs LDA [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=13&ved=0CDIQFjACOAo&url=http%3A%2F%2Fwww.cse.unr.edu%2F~bebis%2FCS790Q%2FLect%2FFR_PCA_LDA.ppt&ei=MWinTpqxGYmZ8QOmg7mjDw&usg=AFQjCNHZBXEM4aTycMA_keqJf-H3GFeFJg], real time [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=17&ved=0CFgQFjAGOAo&url=http%3A%2F%2Fwww.ee.pdx.edu%2F~mperkows%2FCLASS_479%2FBiometrics%2FFaceRecognition%2FRT-face-recognition.ppt&ei=MWinTpqxGYmZ8QOmg7mjDw&usg=AFQjCNEm-k184vGR6sfgSHb2m149iimYbA]
* face recognition [http://www.umiacs.umd.edu/~joseph/face-recognition.pdf], [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=7&ved=0CGAQFjAG&url=http%3A%2F%2Fwww.scourge.fr%2Fmathdesc%2Fdocuments%2Ffacerecog%2Ffinal.ppt&ei=2GGnTvz7J4Ol8QOx89TeDw&usg=AFQjCNH7rmVmML_FYbrBMFEPtI9JSBwS8A], PCA vs LDA [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=13&ved=0CDIQFjACOAo&url=http%3A%2F%2Fwww.cse.unr.edu%2F~bebis%2FCS790Q%2FLect%2FFR_PCA_LDA.ppt&ei=MWinTpqxGYmZ8QOmg7mjDw&usg=AFQjCNHZBXEM4aTycMA_keqJf-H3GFeFJg], real time [http://www.google.es/url?sa=t&rct=j&q=face%20detection%20ppt&source=web&cd=17&ved=0CFgQFjAGOAo&url=http%3A%2F%2Fwww.ee.pdx.edu%2F~mperkows%2FCLASS_479%2FBiometrics%2FFaceRecognition%2FRT-face-recognition.ppt&ei=MWinTpqxGYmZ8QOmg7mjDw&usg=AFQjCNEm-k184vGR6sfgSHb2m149iimYbA], dynamic face recognition 1999 [http://www.google.es/url?sa=t&rct=j&q=dynamic%20face%20recognition&source=web&cd=5&ved=0CFMQFjAE&url=http%3A%2F%2Fwww.ee.pdx.edu%2F~mperkows%2FCLASS_479%2FBiometrics%2FFaceRecognition%2FDynamic-face-recognition.ppt&ei=UG-xTqirL8rH8gPy6vHRAQ&usg=AFQjCNExAs_JkxAQX8l4Hp78YPUwrEyseQ]


== robotica general ==
== robotica general ==
Línea 31: Línea 34:


* [http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/how-google-self-driving-car-works como funciona el coche de google]
* [http://spectrum.ieee.org/automaton/robotics/artificial-intelligence/how-google-self-driving-car-works como funciona el coche de google]
* pagina de proyectos abiertos de SLAM [http://openslam.org/]
* SLAM Summer School 2006 [http://www.robots.ox.ac.uk/~SSS06/Website/index.html]
*SLAM curso de Cyrill Stachniss [http://ais.informatik.uni-freiburg.de/teaching/ws13/mapping/]
* http://bair.berkeley.edu/blog/2017/06/27/dexnet-2.0/
== optical flow ==
* CMU course introduction to optical flow [http://www.google.es/url?sa=t&rct=j&q=face%20tracking%20ppt&source=web&cd=8&ved=0CGMQFjAH&url=http%3A%2F%2Fwww.cs.cmu.edu%2Fafs%2Fcs%2Facademic%2Fclass%2F15385-s06%2Flectures%2Fppts%2Flec-16.ppt&ei=GEaxTon5FcK48gPxu5nOAQ&usg=AFQjCNHzTQ33kJfmWJUf1OppPLZr9YTsWw]
== tracking ==
* tracking motion, S. Thrun [http://www.google.es/url?sa=t&rct=j&q=tacking%20thrun%20ppt&source=web&cd=1&ved=0CB0QFjAA&url=http%3A%2F%2Frobots.stanford.edu%2Fcs223b07%2Fnotes%2FCS223B-L12-Tracking.ppt&ei=AlOxTvinJYXf8QOhkrSuAQ&usg=AFQjCNFgwv20W_DV9aDgyLCW7G2eenmRQw], [http://www.google.es/url?sa=t&rct=j&q=tacking%20thrun%20ppt&source=web&cd=2&ved=0CCMQFjAB&url=http%3A%2F%2Frobots.stanford.edu%2Fcs223b06%2Fnotes%2FCS%2520223-B%2520L11%2520Filters.ppt&ei=AlOxTvinJYXf8QOhkrSuAQ&usg=AFQjCNGiRAIXw7G4t4DAtZSZq5kYzM4euw], [http://www.google.es/url?sa=t&rct=j&q=tacking%20thrun%20ppt&source=web&cd=3&ved=0CCwQFjAC&url=http%3A%2F%2Frobots.stanford.edu%2Fcs223b05%2Fnotes%2FCS%2520223-B%2520L12%2520Filters.ppt&ei=AlOxTvinJYXf8QOhkrSuAQ&usg=AFQjCNEtTWZefCe1ezN9gvh-OJ7zW-fqog]
* particle filters [http://web.me.com/dellaert/07F-Vision/Schedule_files/11-ParticleFilters.ppt.pdf]
* [http://www.cs.unc.edu/~welch/kalman/ kalman filter]
* ratones [http://www.mousemotorlab.org/deeplabcut/]


== environmental sensing ==
== environmental sensing ==


*[http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1526904 operación Neptuno: sensorización oceánica]
*[http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=1526904 operación Neptuno: sensorización oceánica]
* ice cube [https://spectrum.ieee.org/tech-talk/aerospace/astrophysics/the-icecube-neutrino-detector-at-the-south-pole-hits-paydirt]


== content based retrieval ==
== content based retrieval ==


* life-log retrieval [http://research.microsoft.com/en-us/um/people/jgemmell/carpe2004/CARPE2004-Aizawa.pdf]
* life-log retrieval [http://research.microsoft.com/en-us/um/people/jgemmell/carpe2004/CARPE2004-Aizawa.pdf]
* learning everything from anything [http://levan.cs.washington.edu/], [http://levan.cs.washington.edu/ngrams/ngrams_web.pdf]
== monitorizacion del entorno ==
* seeing around corners [https://spectrum.ieee.org/tech-talk/consumer-electronics/audiovideo/mit-shows-how-smartphones-could-peek-around-corners]


== imagen medica ==
== imagen medica ==


* [http://www.fmrib.ox.ac.uk/Members/karla/lectures-and-teaching-material Teaching material Karla Miller from fMRIB Univ. Oxford]
* curso de FSL [http://fsl.fmrib.ox.ac.uk/fslcourse/]


* un prezi de MRI y fMRI [http://prezi.com/goiorwi3w-bl/quick-intro-to-mri-and-fmri/]
* un prezi de MRI y fMRI [http://prezi.com/goiorwi3w-bl/quick-intro-to-mri-and-fmri/]
Línea 49: Línea 82:


* [[media:Presentacion-articulo-staal-2007.pdf|  segmentacion de vasos en retina]]
* [[media:Presentacion-articulo-staal-2007.pdf|  segmentacion de vasos en retina]]
* [[Media:On_dti_models_20110112.pdf | Slides sobre Modelos de difusión para imagen de tensor de difusión (DTI)]]
* [[Media:IntroMaster2012.pdf | Introduccion al Análisis de Imagenes Cerebrales]]
* [[Media:PracticaVBM.pdf | Voxel Based Morphometry]]


== finanzas ==
== finanzas ==
Línea 100: Línea 139:
* [http://www.youtube.com/watch?v=SBKS_OiBzP4 dicen que funciona en Heathrow ¿?]
* [http://www.youtube.com/watch?v=SBKS_OiBzP4 dicen que funciona en Heathrow ¿?]


== MObile robotics ==
== Mobile robotics ==


* [http://www.youtube.com/watch?v=oDgr80cGwPQ  DARPA Grand Challenge]
* [http://www.youtube.com/watch?v=oDgr80cGwPQ  DARPA Grand Challenge]
* [http://www.youtube.com/watch?v=TDqzyd7fDRc Sebastian THrun explicando como ganar el Grand Challenge]
* [http://www.youtube.com/watch?v=TDqzyd7fDRc Sebastian THrun explicando como ganar el Grand Challenge]
* [http://www.youtube.com/watch?v=I_ZjnfBKqoI pedestrian detection]
* un helicoptero haciendo SLAM [http://techtv.mit.edu/videos/4149-indoor-autonomous-helicopter]
* un curso de SLAM [http://www.youtube.com/watch?v=V9qQc5X7O0k]
* coleccion de videos de SLAM de Freiburg university [http://www.youtube.com/watch?v=NUtMBog7gDI&list=PLC02EB07AE2E1DB06]
== structure from motion ==
[http://www.youtube.com/watch?v=2eaGwk4Xhks demo CBIT 2003]
[http://www.youtube.com/watch?v=v4fBSbEqtSs&feature=related presentacion univ. Girona underwater]


== narices electronicas ==
== narices electronicas ==


* [http://www.youtube.com/watch?v=oXpLdSjPkik narices electrónicas para la detección de cancer]
* [http://www.youtube.com/watch?v=oXpLdSjPkik narices electrónicas para la detección de cancer]
== human computer interaction ==
[http://www.youtube.com/watch?v=B4dwu3si9x0 hand gesture recognition OpenCV]
[http://www.youtube.com/watch?v=os4wiUivXNw hands free 3d interface]
== content based image retrieval ==
* [http://www.youtube.com/watch?v=iWD0IyK9ddw demo de un sistema sencillo en matlab]
* [http://www.youtube.com/watch?v=2eaGwk4Xhks flexible image retrival based on image parts]
== Imagen Médica ==
* [http://www.youtube.com/watch?v=r5ODmPu9if8 Cell diffusion]
* [http://www.youtube.com/watch?v=H7QsDs8ZRMI Intro to diffusion]
* [http://www.youtube.com/watch?v=GCCCSWtaqJY Diffusion in brain tissues]
* [http://www.youtube.com/watch?v=PpoJQw4WSn8 Slideshow of a series of diffusion weighted images]
* [http://www.youtube.com/watch?v=6HZwCuN_P_0 Brain principal diffusion directions]
* [http://www.youtube.com/watch?v=8TAmyOAkCz8 Tractografía cerebral]
* [http://www.youtube.com/watch?v=TxlV50P6NEI The Human Connectome project]


= Referencias de grupos de investigacion =
= Referencias de grupos de investigacion =
Línea 120: Línea 202:


* [http://www.stanford.edu/class/ee368/Project_11/index.html Standford digital image processing final projects]
* [http://www.stanford.edu/class/ee368/Project_11/index.html Standford digital image processing final projects]
* [http://www.cse.unr.edu/~bebis/CS679/ UNR course on pattern recognition]


* [http://www.lis.inpg.fr/pages_perso/herault/ Jeanny Herault, Grenoble]
* [http://www.lis.inpg.fr/pages_perso/herault/ Jeanny Herault, Grenoble]
Línea 130: Línea 214:
* Scilab
* Scilab
* demo de algoritmos de clustering en java [http://www.ehu.es/ccwintco/groupware/index.php?menuaction=phpbrain.uikb.view_article&art_id=130]
* demo de algoritmos de clustering en java [http://www.ehu.es/ccwintco/groupware/index.php?menuaction=phpbrain.uikb.view_article&art_id=130]
* recursos en R para neuroimagen [http://johnmuschelli.com/Neuroimaging_in_R/index.html#1] [http://johnmuschelli.com/neuroc_talk/Pitt_Stats_in_Imaging.html#1]
* proceso de imagenes de patologia celular [https://github.com/qupath/qupath/blob/master/README.md]
* calibracion multicamara [http://cmp.felk.cvut.cz/~svoboda/SelfCal/]
* software y datos multispectrales HYDICE [https://www.erdc.usace.army.mil/Media/Fact-Sheets/Fact-Sheet-Article-View/Article/610433/hypercube/]

Revisión actual - 12:40 8 oct 2018

referencias generales

  • visual recognition, tutorial AAAI 08 [1]

Refencias de revistas y presentaciones

face detection and recognition

robotica general

  • pagina de proyectos abiertos de SLAM [19]
  • SLAM Summer School 2006 [20]
  • SLAM curso de Cyrill Stachniss [21]

optical flow

  • CMU course introduction to optical flow [22]

tracking

  • particle filters [26]

environmental sensing

content based retrieval

  • life-log retrieval [29]
  • learning everything from anything [30], [31]

monitorizacion del entorno

  • seeing around corners [32]

imagen medica

  • un prezi de MRI y fMRI [34]
  • curso SPM de 2008 [35]

finanzas

  • trading at the speed of light [36]

Videos

Image Processing

proceso de caras

tracking

reconocimiento de huellas

reconocimiento de iris

Mobile robotics

  • un helicoptero haciendo SLAM [37]
  • un curso de SLAM [38]
  • coleccion de videos de SLAM de Freiburg university [39]

structure from motion

demo CBIT 2003

presentacion univ. Girona underwater

narices electronicas

human computer interaction

hand gesture recognition OpenCV

hands free 3d interface

content based image retrieval

Imagen Médica

Referencias de grupos de investigacion

Recursos software

  • Matlab, Image Processing Toolbox
  • Photoshop
  • ImageJ [40]
  • Scilab
  • demo de algoritmos de clustering en java [41]
  • recursos en R para neuroimagen [42] [43]
  • proceso de imagenes de patologia celular [44]
  • calibracion multicamara [45]
  • software y datos multispectrales HYDICE [46]