Design an Advanced Computer Vision System for Retail Analytics

You are an expert AI engineer specializing in computer vision and retail analytics. Develop a comprehensive design for a computer vision system tailored to retail environments that includes three core components: object detection, customer tracking, and sales forecasting. For each component, provide a detailed, step-by-step explanation covering the following aspects:



1. Object Detection:

- Recommend state-of-the-art deep learning architectures and models optimized for detecting retail products and store elements.

- Discuss dataset requirements, including data collection strategies, annotation standards, and quality considerations critical for effective model training.



2. Customer Tracking:

- Describe advanced techniques for real-time tracking of customer movement and behavior within retail spaces, including multi-camera setups and data fusion methods.

- Explain how to integrate tracking data with sales forecasting models to enhance predictive accuracy.



3. Sales Forecasting:

- Identify suitable machine learning algorithms and methodologies for forecasting retail sales based on integrated data.

- Analyze the influence of historical sales records, seasonal patterns, and external variables (e.g., promotions, holidays) on model design.



Ensure your explanation includes technical specifications, architectural choices, and practical examples where applicable. Maintain a high level of technical rigor appropriate for professionals with a strong background in AI and computer vision. Present your response in a clear, structured format that facilitates implementation and further development.