Video Processing and Standards Conversion
This lecture Video Processing and Standards Conversion that has many applications in video denoising, video interpolation and de-interlacing. It covers the following topics in detail: Continouous and discrete multidimensional signals. Multidimensional FIR and IIR Systems. Multidimensional signal transforms (Z transform, DFT) and convolution support. Various types of temporal, spatial, spatiotemporal and adaptive video denoising. Motion-compensated video filtering. Video interpolation, format conversion and de-interlacing.
Video Quality
This lecture overviews Video Quality that has many applications in cinema movies, digital TV and video streaming. It covers the following topics in detail: Video Quality Assessment Methods. Subjective Quality Assessment: MOS, DMOS and Preference factor (PF). Objective Quality Assessment Metrics: Psychophysical Metrics, Engineering Metrics and Methods (PEVQ, Pixel – based Metrics, VMAF). Camera image quality in cameras.
Moving Image Perception
This lecture overviews Moving Image Perception that has many applications in video acquisition, processing and coding. It covers the following topics in detail: Human Vision Modeling. Video Frequency Content, (spatial, temporal and spatiotemporal frequencies). Spatiotemporal HVS Models (Kelly experiments, spatiotemporal contrast sensitivity, saccadic movements, Smooth eye pursuit movement). Video Quality Assessment.
Video Digitization
This lecture overviews Video Digitization that has many applications in digital video and TV. It covers the following topics in detail: Video scanning and sampling. 3D data types (Digital video signal, volumetric images). Progressive/Interlaced video sampling. 2D sampled image spectrum. Reconstruction of analog video. General video sampling grids: interlaced, quincunx, orthorhombic grids. General analog video sampling, spectrum and reconstruction.
Introduction to Video Processing and Analysis
This lecture overviews Video Processing and Analysis that has many applications in digital TV, video streaming, video conferencing and social media, to mention a few applications. It covers the following topics in detail: Video sampling and digitization, Visual Moving Image Perception, Video filtering, Motion Estimation 2D visual object tracking, Video Compression, Video indexing and retrieval, Video Summarization, Video Captioning, Video description.
Hidden Markov Models
This lecture overviews Hidden Markov Models that have many applications in Data Analytics and Signal Analysis. It covers the following topics in detail: Markov Chains. Hidden Markov Chains: Viterbi algorithm, Forward-backward algorithm. HMMs applications: Speech recognition, Name-entity recognition, Human Action Recognition, Gesture recognition.