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Security AI · Human movement analysis

Moving / Stopped Persons Detection

An open-source computer vision system for real-time and post-event human movement analysis, detecting people and distinguishing between moving, stopped, and newly appeared individuals.

ROLEComputer Vision Engineer TYPEOpen source project STATUSPublished

The challenge

Detect people in dynamic scenes

Identify individuals across diverse environments in real time or from recorded video.

Separate movement states

Distinguish between people who are moving, stopped, or newly detected in the frame.

Support security use cases

Flag stationary individuals whose prolonged stillness may require operator attention.

The approach

01

Person detection with YOLO

Used Ultralytics YOLOv8 / YOLOv10 to detect people across video frames.

02

Tracking and movement analysis

Used Roboflow Supervision to analyze displacement and classify motion behavior.

03

Absolute and relative thresholds

Implemented both absolute speed and relative speed threshold variants.

04

Scenario-based outputs

Separated combined moving/stopped detection, moving-only, and stopped-only workflows.

Outcomes

3 states

Movement classification

Moving, stopped, and under-processing states.

4 parts

Scenario implementation

Absolute, relative, moving-only, and stopped-only workflows.

Security-ready

Stationary behavior monitoring

Designed for use cases where prolonged stillness may need attention.

Stack YOLOv8 YOLOv10 Ultralytics Roboflow Supervision Python Object Detection Video Analytics Motion Analysis