Computer Vision: From 3D Reconstruction to Visual Recognition

开始时间: 04/22/2022 持续时间: 未知

所在平台: CourseraArchive

课程类别: 计算机科学

大学或机构: Stanford University（斯坦福大学）

授课老师： Fei-Fei Li Silvio Savarese

课程主页: https://www.coursera.org/course/computervision

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课程详情

When a 3-dimensional world is projected onto a 2-dimensional image, such as the human retina or a photograph, reconstructing back the layout and contents of the real-world becomes an ill-posed problem that is extremely difficult to solve. Humans possess the remarkable ability to navigate and understand the visual world by solving the inversion problem going from 2D to 3D. Computer Vision, a modern discipline of artificial intelligence, seeks to imitate such abilities of humans to recognize objects, navigate scenes, reconstruct layouts, and understand the geometric space and semantic meaning of the visual world. These abilities are critical in many applications including personal robotics, autonomous driving and exploration as well as photo organization, image or video retrieval and human-computer interaction.

This course delivers a systematic overview of computer vision, comparable to an advanced graduate level class. We emphasize on two key issues in modeling vision: space and meaning. We begin by laying out the main problems vision needs to solve: mapping out the 3D structure of objects and scenes, recognizing objects, segmenting objects, recognizing meaning of scenes, understanding movements of humans, etc. Motivated by these important problems centered on the understanding of space and meaning, we will study the fundamental theories and important algorithms of computer vision together, starting from the analysis of 2D images, and culminating in the holistic understanding of a 3D scene

课程大纲

Part 0: Introduction - What is computer vision?

Part 1: Visual understanding in 2D space

pixels

groups of pixels

object and scene recognition

video features

Part 2: Perceiving and modeling the 3D space

capturing a picture in 3D

popping out a scene in 3D

popping out an object in 3D

mapping out a space

Part 3: Coherent understanding of the scene and the 3D space

object recognition in 3D space

visual recognition in context

Part 4: Functions and activities in the 3D scene

event recognition in images

action recognition in videos

vision and language

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课程简介

This course delivers a systematic overview of computer vision, emphasizing two key issues in modeling vision: space and meaning. We will study the fundamental theories and important algorithms of computer vision together, starting from the analysis of 2D images, and culminating in the holistic understanding of a 3D scene.