Roboflow | Dwell Time Analysis with Computer Vision | Real-Time Stream Processing @Roboflow | Uploaded 6 months ago | Updated 3 hours ago
Learn how to use computer vision to analyze wait times and optimize processes. This tutorial covers object detection, tracking, and calculating time spent in designated zones. Use these techniques to improve customer experience in retail, traffic management, or other scenarios.

Chapters:

- 00:00 Intro
- 00:41 Static File Processing vs. Stream Processing: Time Calculation Explained
- 04:29 Time Calculation Methods: FPS vs. ClockTime
- 06:54 Project Setup
- 08:39 Object Detection and Tracking
- 12:57 Defining Zones: How to Filter Objects
- 16:33 Measuring Time
- 17:44 Why Naive Stream Processing Fails
- 21:02 Efficient Stream Processing
- 24:19 Important Considerations
- 26:07 Outro

Resources:

- Roboflow: roboflow.com

- 🔴 Community Session April 11 2024 at 08:00 AM PST / 11:00 AM EST / 05:00 PM CET: youtube.com/watch?v=u7XUC-3TqY8

- ⭐ Inference GitHub: github.com/roboflow/inference
- ⭐ Supervision GitHub: github.com/roboflow/supervision

- 💻 Time in Zone Code: github.com/roboflow/supervision/tree/develop/examples/time_in_zone
- 🌇 MS COCO Dataset on Roboflow Universe: universe.roboflow.com/microsoft/coco/dataset/5
- 📙Detect and Annotate Supervision Guide: supervision.roboflow.com/develop/how_to/detect_and_annotate/#annotate-image-with-segmentations

- 🎬 Source Checkouts Video: youtube.com/watch?v=-8zyEwAa50Q
- 🎬 Source Traffic Video: youtube.com/watch?v=MNn9qKG2UFI

Stay updated with the projects I'm working on at github.com/roboflow and github.com/SkalskiP! ⭐