Object and people tracking across video

Tracking gives each object an identity as it moves through video, so you can count entries, measure how long things stay, and understand flow instead of seeing only single snapshots.

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What we build

Object Tracking Development: what you get

Multi-object tracking with stable IDs across frames
Line-crossing and zone entry and exit counting
Dwell time and queue length measurement
Path and heat-map analysis of movement
Handling of occlusion, crowds and camera changes
Anonymised statistics when you do not need to identify individuals

This is a good fit if…

You count people, vehicles or items passing a point
You need to know how long things wait or how they move
Manual counting is costly or inaccurate

Typical uses

Count visitors entering and leaving
Measure queue length and waiting time
Show how vehicles move through a yard or car park

How it works

A simple process, no surprises

1
Discovery
We study your camera views and what you want counted or timed.
2
Scope and plan
We agree counting lines, zones and privacy rules for what is stored.
3
Build and review
We build and test on your own footage, comparing counts with manual checks.
4
Deliver and support
We deliver dashboards and exports and tune the system for busy and quiet periods.

Technologies we use for this

Python
OpenCV
ByteTrack-style trackers
YOLO
ONNX / TensorRT
Dashboards

Reviews

What clients say

★★★★★

“They took a task my team repeated every week and turned it into a single button. Clear communication throughout, and the handover documentation meant we could use it straight away”

James · Managervia Fiverr

FAQ

Object Tracking Development: common questions

Does tracking identify individual people?+

It follows objects as shapes in video to count and measure movement. It can be designed to keep results anonymous and avoid storing faces. We discuss privacy and local rules with you at the start.

How accurate is the counting?+

Accuracy depends on camera angle, crowding and lighting. We measure it on your own footage and agree a target before deployment.

Can it work across several cameras?+

Yes. Multi-camera setups are possible, though following one object between different cameras is harder and depends on the layout.

From the blog

Camera frame of an industrial scene with labelled bounding boxes around parts, linked to icons for a dataset, a neural network and an edge device.

Computer Vision / AI

Custom Object Detection Models: Data, Training and Deployment

What it typically takes to build a custom object detection model, from collecting and labelling data to training, evaluation and running it on edge or cloud hardware.

11 Oct 2026 · 5 min read

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Need object tracking development?

Tell us what you want to count or time on camera, and we will suggest how to measure it.

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