m (Labs - CG)
 
(44 intermediate revisions by 3 users not shown)
Line 9: Line 9:
 
__TOC__
 
__TOC__
  
; Lecture
+
; Lectures
: Wednesday 9:50, M-I
+
:[[Martin Madaras|Martin Madaras]]
 +
:[[Zuzana Berger Haladova|Zuzana Berger Haladová]]
 +
 
 
; Excercises
 
; Excercises
: Monday 18:10, F1-248
+
: [[Zuzana Berger Haladova|Zuzana Berger Haladová]]
  
 
=== Grading ===
 
=== Grading ===
Line 18: Line 20:
 
* Final writen exam: 50p
 
* Final writen exam: 50p
 
* Excercises: 50p ''(with minimum of 30p)''
 
* Excercises: 50p ''(with minimum of 30p)''
** 4 home assignments: 4x10p (2 from CG part and 2 from IP)
+
** 2 home assignments (projects): 2x20p (1 from CG part and 1 from IP part)
 
** Attendance: 10x1p
 
** Attendance: 10x1p
 
                                        
 
                                        
Line 28: Line 30:
  
 
----
 
----
 +
== Lectures ==
 +
*21.9. Intro [https://docs.google.com/presentation/d/1zcsOFvFzUtIWBN_OnsM2GDpiO11TeOwg8bhsihzDnPI/edit?usp=sharing slides]
 +
*28.9. - 26.10. CG [http://www.sccg.sk/~madaras/students.html CG slides ]
 +
*9.11.  Snimanie obrazu [https://docs.google.com/presentation/d/1mxQZt2V2fwaNZlZ2c4QVOXlJunyBBbGRfIv68yjBZXQ/edit?usp=sharing slides]
 +
*16.11. Predspracovanie [https://docs.google.com/presentation/d/1JHeZS8IlN41tR_7KbLc_6KDX_qKnLIBN_I6mb82mlyw/edit?usp=sharing slides]
 +
*23.11. Segmentacia [https://docs.google.com/presentation/d/1Rgos4gePcXCjhmhwu-DUto18yKvQrUifJZnnr8k2-ms/edit?usp=sharing slides]
 +
*30.11. Image classification and Pattern recognition [https://docs.google.com/presentation/d/1uXw1ATBRvj6P2426PE0Mejpb2TksVrsu-xOiJkWTIL0/edit?usp=sharing slides]
 +
*7.12. Deep learning for computer vision, [https://docs.google.com/presentation/d/1aZ0iLF1DM8TtB_J6rGyWVRGHP7EhJiTeQeWlV3z7pVE/edit?usp=sharing slides]
 +
*14.12. Exam
 +
<!---
 +
[http://www.sccg.sk/~madaras/students.html CG slides ]
 +
*3.11. Snimanie [https://docs.google.com/presentation/d/1mxQZt2V2fwaNZlZ2c4QVOXlJunyBBbGRfIv68yjBZXQ/edit?usp=sharing slides]
 +
*10.11. Predspracovanie [https://docs.google.com/presentation/d/1JHeZS8IlN41tR_7KbLc_6KDX_qKnLIBN_I6mb82mlyw/edit?usp=sharing slides]
 +
*24.11. Segmentacia [https://docs.google.com/presentation/d/1Rgos4gePcXCjhmhwu-DUto18yKvQrUifJZnnr8k2-ms/edit?usp=sharing slides]
 +
*1.12. Image classification and Pattern recognition [https://docs.google.com/presentation/d/1uXw1ATBRvj6P2426PE0Mejpb2TksVrsu-xOiJkWTIL0/edit?usp=sharing slides]
 +
*8.12. Deep learning for computer vision, online cez Teams [https://docs.google.com/presentation/d/1aZ0iLF1DM8TtB_J6rGyWVRGHP7EhJiTeQeWlV3z7pVE/edit?usp=sharing slides]
 +
*15.12. Exam, online cez Teams
 +
--->
 +
== Labs ==
 +
Points [https://docs.google.com/spreadsheets/d/12DMrmDswrCqdNMd-02RpbbzofmYk-PGfbWB-kJwHDBA/edit?usp=sharing table]
  
 +
CV [https://docs.google.com/document/d/1JLmTNcAQLi0XtcyTqTcvGExXptJaMH0rnbhYgAyROcU/edit?usp=sharing] Assignment due to 6.12.2022 6:00
  
= Labs - CG =
+
*22.9. Lab excursion
 +
*29.9. Exercise 1 CG [https://docs.google.com/presentation/d/1v7SWRgfa1ihLjcLxeIUGDVAIWeBjlNwjrpkxrvv1q9Q/edit?usp=sharing slides]
 +
*6.10. Exercise 2 CG [https://docs.google.com/presentation/d/1DK8_GjOTbYONvwXiauMT6ABQHNY5o69ZtnxmTRfyCnA/edit?usp=sharing slides]
 +
*13.10. Exercise 3 CG [https://docs.google.com/presentation/d/1BmfyQmPth4GvzD1eiWJUQSnnixTFWO4dph61pYDa-74/edit?usp=sharing slides] [https://docs.google.com/document/d/1ZSI6C04qPN8x4UOT_FjYGv4djwlp46LPBz7-Q4JsG3Q/edit?usp=sharing priklad na DDA]
 +
*20.10. Exercise 4 CG [https://docs.google.com/presentation/d/1mY9Q2QLoMn1Q0nIR6DzQeiyBpnOlFvKKY-kwlpaKjT4/edit?usp=sharing slides]
 +
*27.10. Exercise 5 CG [https://docs.google.com/presentation/d/17MbGgSry_JtmCclZ_Tr-Rin9scmMT9UZVQIjas5O7u0/edit?usp=sharing slides]
 +
*3.11. Consultations online
 +
*10.11. Exercise 1 CV [https://docs.google.com/presentation/d/1ycSRkd3tuj-sOjRaanrYTvQHcZkOSs_yCIkNjkwfMpg/edit?usp=sharing slides] [https://drive.google.com/file/d/1uGdO1Q_WsrIU2rjWS9UgO2IbBTqvxEYY/view?usp=sharing data] [https://drive.google.com/file/d/14SPrH_jBEeTN2nMx0NfL8vfmBxsvr6y7/view?usp=sharing bonus]
 +
*17.11. Holiday Exercise 2 CV (Recorded) [https://docs.google.com/presentation/d/1IxgO-uLd8jyOrTP-U0qUJduffgmuMriiJEoaP0iHZb0/edit?usp=sharing slides] [https://liveuniba-my.sharepoint.com/:v:/g/personal/haladova2_uniba_sk/EVhx3n6HMnNHvTdKTJqqSXABRDkIHLgCu1NlVo4EqGKknA?e=zKf4nY video]
 +
*24.11. Exercise 3 CV [https://docs.google.com/presentation/d/1TukhOGCl7tRNWbIWEXiJQiUxk_oye-7sWHju60ihjEM/edit?usp=sharing slides][https://drive.google.com/file/d/1kRJpC3xL1AEVwYM15rIu2ciQldg1Muiu/view?usp=sharing data]
 +
*1.12. Exercise 4 CV [https://docs.google.com/presentation/d/1VkKJjRB_FeBDZ_qaThgnPyMKejxmuGAV4824MXddk_Y/edit?usp=sharing slides] [https://drive.google.com/file/d/1GaLXdzw62I3HRvcZwTyfRk9tEaAHiXpV/view?usp=sharing data]
 +
*8.12. Exercise 5 CV [https://docs.google.com/presentation/d/1MqMF7ocu4A6IaQ29CHzCdJhZstINlf8AGBDINS2Ns9U/edit?usp=sharing slides]
 +
*15.12. Consultations online 
 +
 
 +
 
 +
<!---
 +
* Slides & project assignment: [https://github.com/danasko/zpgso GitHub]
  
 
Guide: Adam Riečický
 
Guide: Adam Riečický
  
 
Mondays at 16:30 on [https://teams.microsoft.com/l/channel/19%3ac7d4a4b8193e42a7ba7bd4c9fbb24599%40thread.tacv2/General?groupId=06d7acf3-8480-4c8f-aa56-6e71fd0ebbb1&tenantId=ce31478d-6e7a-4ce7-8670-a5b9d51884f9 Teams]
 
Mondays at 16:30 on [https://teams.microsoft.com/l/channel/19%3ac7d4a4b8193e42a7ba7bd4c9fbb24599%40thread.tacv2/General?groupId=06d7acf3-8480-4c8f-aa56-6e71fd0ebbb1&tenantId=ce31478d-6e7a-4ce7-8670-a5b9d51884f9 Teams]
<!----
+
 
 
== Slides ==
 
== Slides ==
  
Line 46: Line 85:
 
[https://docs.google.com/presentation/d/1IXT5HbH1q7LhgGfYJkI5khzezfBqzTT1jnp3d15VWGY/edit#slide=id.p Slides #04]
 
[https://docs.google.com/presentation/d/1IXT5HbH1q7LhgGfYJkI5khzezfBqzTT1jnp3d15VWGY/edit#slide=id.p Slides #04]
  
[https://docs.google.com/presentation/d/1y2rWsXCrkgj68UuLU-ELztN57ofnoie7oG5DmgUJXKI/edit#slide=id.g29c1b949f2_0_0 Slides #05]---->
+
[https://docs.google.com/presentation/d/1y2rWsXCrkgj68UuLU-ELztN57ofnoie7oG5DmgUJXKI/edit#slide=id.g29c1b949f2_0_0 Slides #05]
 +
 
 
== Project ==
 
== Project ==
  
Line 69: Line 109:
  
 
=== Stage 2 (10p) ===
 
=== Stage 2 (10p) ===
''Deadline 13.12.2020 23:59''
+
''Deadline 22.12.2020 23:59''
  
 
Add transformation controls to your tool.
 
Add transformation controls to your tool.
Line 88: Line 128:
  
 
=== Stage 3 (7p) ===
 
=== Stage 3 (7p) ===
''Deadline 13.1.2021 23:59''
+
''Deadline 27.1.2021 23:59''
  
 
Enhance existing visualization tool by implementing Blinn-Phong Lightning Model
 
Enhance existing visualization tool by implementing Blinn-Phong Lightning Model
Line 102: Line 142:
 
: [https://dai.fmph.uniba.sk/upload/b/bd/Zpgso_pr2_scr1.png screen 1]
 
: [https://dai.fmph.uniba.sk/upload/b/bd/Zpgso_pr2_scr1.png screen 1]
 
: [https://dai.fmph.uniba.sk/upload/7/71/Zpgso_pr2_scr2.png screen 2]
 
: [https://dai.fmph.uniba.sk/upload/7/71/Zpgso_pr2_scr2.png screen 2]
 +
 +
=== Bonus Points ===
 +
''Submit with Stage 3''
 +
 +
Extend your visualization options by the following features to earn bonus points. Attention: Your point total (including bonus points) will not exceed 25 points for exercises from computer graphics part.
 +
 +
; Material Properties (1p)
 +
: Expose material properties ka, kd, ks, shininess, and color to GUI. Re-render image when the user changes these properties.
 +
 +
; Lighting Model Selection (2p)
 +
: Implement a switch that allows the selection between two lighting models (Phong vs Blin-Phong). The difference should be minimal but it is a proof of concept.
 +
 +
; Light Types (3p)
 +
: Add possibility to select the light type (point light, sun/directional light) - the GUI option should also change from "light direction" to "light position".
 +
--->

Latest revision as of 18:36, 7 January 2023

Fundamentals of Computer Graphics and Image Processing 1-AIN-301

Course information sheet >

Lectures
Martin Madaras
Zuzana Berger Haladová
Excercises
Zuzana Berger Haladová

Grading

You can get 100 points (p) during semester, where 1pt = 1% of final grade

  • Final writen exam: 50p
  • Excercises: 50p (with minimum of 30p)
    • 2 home assignments (projects): 2x20p (1 from CG part and 1 from IP part)
    • Attendance: 10x1p

Materials



Lectures

  • 21.9. Intro slides
  • 28.9. - 26.10. CG CG slides
  • 9.11. Snimanie obrazu slides
  • 16.11. Predspracovanie slides
  • 23.11. Segmentacia slides
  • 30.11. Image classification and Pattern recognition slides
  • 7.12. Deep learning for computer vision, slides
  • 14.12. Exam

Labs

Points table

CV [1] Assignment due to 6.12.2022 6:00