Imaging sciences Overview Image sciences Computer vision Extracting information

Imaging sciences overview image sciences computer

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Imaging sciences – Overview Image sciences Computer vision: Extracting information from images/videos Image/Video processing: Producing new images/videos from input images/videos 25
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Imaging sciences – Image processing and computer vision Spectrum from image processing to computer vision 26
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Imaging sciences – Image processing Image processing (Source: Iasonas Kokkinos) Image processing: define a new image from an existing one Video processing: same problems + motion information 27
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Imaging sciences – Image processing Image processing (Source: Iasonas Kokkinos) Image processing: define a new image from an existing one Video processing: same problems + motion information 27
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Imaging sciences – Image processing Image processing – Geometric transform Geometric transform Change pixel location 28
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Imaging sciences – Image processing Image processing – Colorimetric transform Colorimetric transform Change pixel values 29
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Imaging sciences – Computer vision Computer vision Definition (The British Machine Vision Association) Computer vision (CV) is concerned with the automatic extraction, analysis and understanding of useful information from a single image or a sequence of images. CV is a subfield of Artificial Intelligence. 30
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Imaging sciences – Computer vision Computer vision – Artificial Intelligence (AI) Definition (Collins dictionary) artificial intelligence, noun : type of computer technology which is concerned with making machines work in an intelligent way, similar to the way that the human mind works. Definition (Oxford dictionary) artificial intelligence, noun : the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation. Remark: CV is a subfield of AI, CV new very best friend is machine learning (ML), ML is also a subfield of AI, but not all computer vision algorithms are ML. 31
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Imaging sciences – Computer vision – Image classification Computer vision – Image classification Goal: to assign a given image into one of the predefined classes. 32
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Imaging sciences – Computer vision – Object detection Computer vision – Object detection (Source: Joseph Redmon) Goal: to detect instances of objects of a certain class (such as human). 33
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Imaging sciences – Computer vision – Image segmentation Computer vision – Image segmentation (Source: Abhijit Kundu) Goal: to partition an image into multiple segments such that pixels in a same segment share certain characteristics (color, texture or semantic). 34
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Imaging sciences – Computer vision – Image captioning Computer vision – Image captioning (Karpathy, Fei-Fei, CVPR, 2015) Goal: to write a sentence that describes what is happening.
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