Materials are available on the educator's website:
https://mrl.cs.vsb.cz//people/fusek/zao_course.html
Materials are also available in LMS:
https://lms.vsb.cz
Fundamentals of Image Processing
| Type of study | Bachelor |
|---|---|
| Language of instruction | English |
| Code | 460-2070/02 |
| Abbreviation | ZAO |
| Course title | Fundamentals of Image Processing |
| Credits | 4 |
| Coordinating department | Department of Computer Science |
| Course coordinator | Ing. Radovan Fusek, Ph.D. |
Osnova předmětu
Lectures:
* Introduction to actual topics in image analysis.
* Image-based driver behavior recognition.
* Analysis of objects in vehicle surroundings, the detection of vehicles, pedestrians, traffic signs, traffic lights.
* Analysis of data gained from the self-driving car sensors.
* Detection and recognition of 3D objects and its application in augmented reality
* Depth data gathering and analysis.
* Object detection in aerial and satellite images, buildings detection, parking lot analysis, smart cities.
* Image-based people identification, biometry.
* Image and video editing with a goal to fake reality, actual and future trends in artificial intelligence in image processing.
Exercises:
* Introduction to the image processing libraries.
* Practice the methods for image-based driver behavior recognition.
* Experiments with the methods for analysis of objects in vehicle surroundings.
* Introduction to the processing of car sensor data.
* Practice the methods for 3D object recognition.
* Experiments with the depth data.
* Experiments with the methods for the parking lot and satellite image analysis.
* Study of recognition techniques for image-based people identification.
* Experiments with image and video editing with a goal to fake reality, introduction to the new trends in artificial intelligence in image processing.
* Introduction to actual topics in image analysis.
* Image-based driver behavior recognition.
* Analysis of objects in vehicle surroundings, the detection of vehicles, pedestrians, traffic signs, traffic lights.
* Analysis of data gained from the self-driving car sensors.
* Detection and recognition of 3D objects and its application in augmented reality
* Depth data gathering and analysis.
* Object detection in aerial and satellite images, buildings detection, parking lot analysis, smart cities.
* Image-based people identification, biometry.
* Image and video editing with a goal to fake reality, actual and future trends in artificial intelligence in image processing.
Exercises:
* Introduction to the image processing libraries.
* Practice the methods for image-based driver behavior recognition.
* Experiments with the methods for analysis of objects in vehicle surroundings.
* Introduction to the processing of car sensor data.
* Practice the methods for 3D object recognition.
* Experiments with the depth data.
* Experiments with the methods for the parking lot and satellite image analysis.
* Study of recognition techniques for image-based people identification.
* Experiments with image and video editing with a goal to fake reality, introduction to the new trends in artificial intelligence in image processing.
E-learning
Povinná literatura
1. Howse, J. and Minichino, J. Learning OpenCV 4 Computer Vision with Python 3, Packt Publishing Limited, (2020)
2. Moeslund, Thomas B. Introduction to video and image processing: Building real systems and applications. Springer, 10.1007/978-1-4471-2503-7, 2012
3. Petrou, M., Petrou, C.: Image Processing: The Fundamentals, Wiley, ISBN-10: 047074586X , ISBN-13: 978-0470745861 , 2010
2. Moeslund, Thomas B. Introduction to video and image processing: Building real systems and applications. Springer, 10.1007/978-1-4471-2503-7, 2012
3. Petrou, M., Petrou, C.: Image Processing: The Fundamentals, Wiley, ISBN-10: 047074586X , ISBN-13: 978-0470745861 , 2010