Computer Vision

Month 1: Introduction to OpenCV and Image Processing

Introduction to computer vision and its applications
Basics of image processing using Python and OpenCV
Image manipulation techniques: resizing, cropping, rotating, etc.
Image filtering techniques: Gaussian, median, bilateral, etc.
Edge detection techniques: Sobel, Canny, etc.
Thresholding techniques: binary, adaptive, Otsu’s, etc.

Month 2: Feature Extraction and Object Detection

Feature extraction techniques: SIFT, SURF, ORB, etc.
Object detection using Haar cascades and HOG descriptors
Object tracking using Kalman filter
Optical flow and motion analysis
Camera calibration and 3D reconstruction using stereo vision

Month 3: Advanced Computer Vision and Deep Learning

Introduction to deep learning for computer vision
Convolutional neural networks (CNNs) for image classification and object detection
Transfer learning and fine-tuning pre-trained models
Deep learning-based face detection and recognition
Real-time object detection using YOLOv3
Image segmentation using U-Net

Computer Vision