Transcription of Computer Vision - University of Cambridge
{{id}} {{{paragraph}}}
Example: tourism industry
Computer Vision - University of Cambridge
ComputerVisionComputerScienceTripos:16 Lecturesby J G Daugman1. computervision;why theyareso di Imagesensing,pixelarrays, Biologicalvisualmechanisms,fromretinato Edgedetectionoperators; Higherbrainvisualmechanisms;streaming; Texture,colour,stereo, ; ers; a setof :facedetectionandrecognition; thiscoursearetointroducetheprinciples,mo delsandapplicationsof com-putervision,as wellas somemechanismsusedin biologicalvisualsystemsthatmay inspiredesignof arti :imageformation,structure,andcoding;edge andfeaturedetection;neuraloperatorsforim ageanalysis;texture,colour,stereo,motion ;waveletmethods forvisualcodingandanalysis;interpretatio nof surfaces,solids,andshapes;datafusion;pro babilisticclassi ers;visualinferenceandlearning.
understand in depth at least one important application domain, such as face recognition, detection, or interpretation ... An image is a two-dimensional optical projection, but the world we wish ... complexity of the problem and the poverty of the data.
Tags:
Information
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document: