This seminar series covers spatial perception of machines. We focus on the role of computer vision and its relevance for design in contemporary contexts and in future scenarios.
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Date | Time | Topic | Lecturer |
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24.03.2021 | 15:00–17:00 | Computer Vision Introduction | FB |
31.03.2021 | 15:00–17:00 | Processing & Media | FB |
07.04.2021 | 15:00–17:00 | Processing & OpenCV | FB |
14.04.2021 | 15:00–17:00Depth Sensing | Machine Learning Deep Vision (Depth Sensing) | FB |
21.04.2021 | 15:00–17:00 | Project | FB |
28.04.2021 | 15:00–17:00 | Project & Presentation | FB |
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Watch the presentation and write down questions and thoughts that come to your mind.
Password: iad2021
📼 IAD-CV-Introduction Video (24.03.2021)
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Philipp Schmitt: Camera Restricta
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📼IAD-CV-Processing & OpenCV Video (07.04.2021)
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📼 IAD-CV-MachineLearning Video (14.04.2021)
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Tasks
Task 0 - Introduction
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Think about additional features you could implement!
Task 4 Brightest Spot Tracking OpenCV
Use OpenCV to track the brightest spot in the image (interactive paint with OpenCV).
opencv.blur(10);
PVector location = opencv.max();
Task 5 Detecting Apples
Use the provided image and mark the green apples in the image. Check out the example code to extract hue values.
Additional: Implement a color picker that directly adapts to the sensed range.
Task 6 Locate Apples
Locate the position of the extracted apples with the contour detection. Try to indicate the position with a circle or directly draw the area.
Additional: Use the apples as input device for the interactive drawing or another application (a game?)
Task 7 Deep Vision
Download and install the Deep Vision library. Try out the examples and get an overview how the framework works by reading the readme.
Task 8 Project
Think about a simple project you could implement with the tools you already know (and Deep Vision).
Document in a few words / sketches
Upload it till the end of today to the filer
Deliverables
Documentation of your work in the provided template together with your code. This should be placed on the server in httpsmb://filerfileredu.ad.zhdk.ch/DDE/BDE_VIAD/01_ABGABEN/21_FS/Sem4_BitsAtomsIV/
80% Attendance during lessons
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