Computer Vision Lecture 2 4 Image Formation Image Sensing Pipeline

Computer Vision Lecture 2 4 Image Formation Image ођ Lecture: computer vision (prof. andreas geiger, university of tübingen)course website with slides, lecture notes, problems and solutions: uni tuebinge. Dynamic range. information loss due to a d conversion. typical image: 8 bit (0~255) the world is hdr and our eyes have great ability to sense it. an exposure bracketed sequence (each picture is a ldr image) hdr imaging: ldrs hdr. tone mapping: hdr ldr.

Computer Vision Pipeline Part 1 The Big Picture By Manning Image formation & image sensing. in this chapter we explore how images are formed and how they are sensed by a computer. understanding image formation is a prerequisite for full understanding of the methods for recovering information from images. in analyzing the process by which a three dimensional world is projected onto a two dimensional. A part of that reflected light goes through an image plane that reaches a sensor plane via optics. fig: 1. photometric image formation (image cr edit: szeliski, computer vision: algorithms and applications 2010) some factors that affect image formation are: the strength and direction of the light emitted from the source. Computer vision lecture 2.2 (image formation: geometric image formation). computer vision lecture 2.3 (image formation: photometric image formation). computer vision lecture 2.4 (image formation: image sensing pipeline). computer vision lecture 3.1 (structure from motion: preliminaries). F number by √2. equals change in aperture area by factor of 2. equals change in amount of light by factor of 2. example: → f 2 f 2.8 → f 4 (each one halves the amount of light) building a real camera: field of view. field of view.