Project3 - TC 247

sketchfab

TC 247 Project 3 - Nick Hess Project Overview: The objective of this project is to develop a high-performance, real-time video analytics system that can process and analyze live video feeds from various sources, including IP cameras and mobile devices. The system should be able to detect and track objects within the video stream, identify patterns and anomalies, and provide alerts and notifications in real-time. Key Features: * High-performance video processing capabilities * Real-time object detection and tracking * Pattern recognition and anomaly detection * Alerts and notifications for critical events System Requirements: The system should be able to handle multiple video feeds from various sources, including IP cameras and mobile devices. The system should also be able to process and analyze live video feeds in real-time, providing alerts and notifications for critical events. Technical Requirements: * High-performance computing hardware (e.g., GPU-accelerated servers) * Real-time video processing software (e.g., OpenCV, FFmpeg) * Object detection and tracking algorithms (e.g., YOLO, SORT) * Pattern recognition and anomaly detection software (e.g., machine learning libraries) Development Plan: The project will be developed in three phases: Phase 1: Requirements gathering and system design Phase 2: Development of the video processing engine Phase 3: Integration and testing of the system Team Roles and Responsibilities: Nick Hess: Project lead, responsible for overall project management and coordination John Doe: Software engineer, responsible for developing the video processing engine Jane Smith: Data scientist, responsible for developing the object detection and tracking algorithms