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Computer Vision - 计算机视觉

计算机视觉Computer VisionVision System
COMP90086 Computer Vision - Assignment 3: Fundamental Matrix Calculation
计算机视觉Computer VisionVision System
In this project you will implement the calculation of a Fundamental matrix using your own algorithms. You can use the keypoint detection and matching approach used in the week 8 Workshop, as well as code for drawing lines on images, but the implementation of the Fundamental Matrix calculation must be your own work.
COMP9517: Computer Vision 2022 Term 3 - Assignment: Image Background Substraction
计算机视觉Computer VisionVision System
This assignment is to familiarise you with basic image processing methods. It also introduces you to common image processing and analysis tasks using OpenCV.
COMP9517: Computer Vision 2022 Term 2 Group Project Specification - Tracking pedestrians and analysing their motion in real-world video recordings
计算机视觉Computer VisionVision System
The goal of this group project is to develop and evaluate a method for tracking pedestrians and analysing their motion in real-world video recordings.
[2022] Fundamentals of Computer Vision - Project 3 Tracking Objects in Videos
计算机视觉Computer VisionVision System
You will first implement the Lucas-Kanade tracker, and then a more computationally efficient version called the Matthew-Baker (or inverse compositional) method
[2022] UNSW - COMP9517 Computer Vision - Lab4 Image Segmentation
计算机视觉Computer VisionVision System
The goal of image segmentation is to assign a label to each pixel in an image, indicating whether it belongs to an object (and which object) or the background. In this lab the MeanShift clustering algorithm and the Watershed algorithm will be used to solve unsupervised image segmentation.
[2022] COMPSCI 773 Intelligent Vision Systems - Assignment2 Camera Calibration
计算机视觉Computer VisionVision System
This assignment will look at the optical distortion free camera calibration components (step 1 and 2) of the full stereo vision pipeline with other components of the pipeline explored in subsequent assignments.
[2022] UNSW - COMP9517 Computer Vision - Lab2 SIFT: Scale-Invariant Feature Transform
计算机视觉Computer VisionVision System
A well-known algorithm in computer vision to detect and describe local features in images is the scale-invariant feature transform (SIFT). Its applications include object recognition, mapping and navigation, image stitching, 3D modelling, object tracking, and others.
[2022] UNSW - COMP9517 Computer Vision - Lab1 Image Processing
计算机视觉Computer VisionVision System
This lab revisits important concepts covered in the Week 1 and Week 2 lectures and aims to make you familiar with implementing specific algorithms.
Computer vision 2022 Assignment 3: Deep Learning for Perception Tasks
计算机视觉Computer VisionVision System
For this exercise, we will provide a demo code showing how to train a network on a small dataset called FashionMinst. Please go through the following tutorials first. You will get a basic understanding about how to train an image classification network in pytorch. You can change the training scheme and the network structure. Please answer the following questions then. You can orginaze your own text and code cell to show the answer of each questions.
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