Motion Estimation Lecture
Nowadays, digital videos are everywhere and revolutionize very many domains, notably:
-Digital Media (video/movie) Content Production and Broadcasting,
-Social Media Streaming and Analytics (g., YouTube),
-Mobile computing and streaming
-Videoconferencing
-Medical/Biological/Dental Imaging and Diagnosis,
-Big Visual Data Analytics,
-Internet and Communications (media broadcasting, streaming).
-Scientific Imaging of any sort, e.g., Physics.
Furthermore, Video Processing and Analysis enables diverse applications, in unison with Computer Vision and Machine Learning:
-Autonomous Systems (cars, drones, vessels) Perception,
-Robotics Perception and Control,
-Intelligent Human-Machine Interaction,
-Anthropocentric (human-centered) Computing,
-Smart Cities/Buildings and Assisted living.
Visual Computing, encompassing Computer Vision and Video Processing and Analysis, coupled with AI (notably Machine Learning and Deep Neural Network) advances hit the news almost every day.
Motion estimation principals will be analyzed. Initiating form 2D and 3D motion models, displacement estimation as well as quality metrics for motion estimation will subsequently be detailed. One of the basic motion estimation techniques, namely block matching, will also be presented, along with three alternative, faster methods. A good overview of deep neural notion estimation will be presented. Phase correlation will be described, next followed by optical flow equation methods. Finally, a brief introduction to object detection and tracking will conclude the lecture.