Page Comparison

Here you will find all the necessary resources for the computer vision input.

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Watch the presentation and write down questions and thoughts that come to your mind! We can discuss them later in the Zoom conference.

📼IAD-CV-Introduction Video

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https://zhdk.zoom.us/j/4710337215

Tuesday 30.03.2020

Depth Sensing (Tuesday 9:00 - 10:00)

Watch the video about depth sensing and on how machines are able to perceive our world.

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📼IAD-CV-DepthSensing Video

• DenseDepth - High Quality Monocular Depth Estimation via Transfer Learning [paper][code]

Zoom Conference (Tuesday 10:00 - 10:30)

Questions, notes and comments.

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This input is about computer vision combined with modern machine learning techniques. It is also an introduction about the topic of machine learning in general. How does a machine learn? How does it see?

Task 7

Download the Deep Vision Library (direct download link) for Processing and install it into your library folder. Try out the examples and see how the library works.

Task 8

Use the FaceDetector Webcam Example and try to combine it with the emotion classifier. To create an emotion detector, use the following code sample:

FERPlusEmotionNetwork emotionNetwork = vision.createFERPlusEmotionClassifier();
emotionNetwork.setup();

// run on a single face
emotionNetwork.run(face)

// run on multiple detected images
emotions = emotionNetwork.runByDetections(testImage, detections);

A Java example on how to combine these two methods you can find here, it is Processing as well, but you may have to adapt it slightly.

Furthermore: Have a look at the Gender & Age prediction example and try to add it to the sketch as well.

Data Analysis and Connection (Friday 13:00-17:00)

• Spatial Interaction Examples

• MQTT / shiftr.io

• Open Sound Control (OSC)

• Wekinator

Task 9

Try to analyze your own set of images and think about what you could use this information for. Use the example provided here.

Task 10

Try out the mouse example to train your own classifier.

• What else could you classify?

• Where do you get the data from?

• How can you include this into your main project?

Content

Please do not share the slides and the content from this page. The images and videos in the presentations are sourced but not licensed.

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