VIS-120 · Embedded Vision
Multi-Camera Synchronisation
Keeping many cameras aligned in time, which is where multi-camera systems usually fail.
Who this course is for
System engineers building multi-camera rigs — surround view, stereo pairs, robotics arrays — whose cameras must agree on time tightly enough for fusion to work.
Prerequisites
Course outline
Day 1 — Time, triggers and clocks
- Why multi-camera systems fail on time before they fail on anything else
- Hardware trigger distribution: fan-out, skew in the wiring itself and termination
- Sensor external-trigger and frame-sync modes; rolling vs global shutter exposure placement
- Clock domains: sensor oscillator, receiver clock, host clock and their drift
- Timestamping at source vs at reception and what each can and cannot prove; PTP context
Day 2 — Topology and bandwidth
- Aggregators and deserializers: channel mapping and virtual-channel assignment
- Bandwidth budgeting across a shared CSI receiver: per-camera modes vs aggregate rate
- Trigger topologies for 2, 4 and 8 cameras and their skew floors
- Exposure-time placement inside the frame period and motion-artifact implications
- Frame identity: index counters, timestamps and detecting a dropped or swapped frame
Day 3 — Measurement and validation
- Estimating inter-camera skew from captured timestamps and visual events
- Drift measurement over minutes and hours; fitting a rate and predicting bound crossings
- Validating camera-to-output mapping through the aggregator
- Injecting timestamp and index faults and measuring stereo/fusion degradation
- Operational checks: detecting sync loss in a fielded system
Hands-on labs
Labs follow the academy model — 35% principles, 20% guided investigation, 45% engineering studio. Every claim you make in a lab is backed by a trace, a counter or a measurement you captured yourself. How we teach
- Lab: Wire a hardware trigger to multiple sensors and verify frame-aligned capture with timestamps and a visual strobe
- Lab: Measure clock drift between free-running cameras over an extended run, fit the drift rate and state when sync bounds would be crossed
- Lab: Validate the full camera-to-output mapping through a deserializer/aggregator and produce the channel map as a document
- Lab: Inject a timestamp offset and a frame-index swap into recorded data; measure the resulting stereo depth error and downstream fusion degradation
This course uses lab hardware. In-person cohorts get boards on the desk; online cohorts get remote board access over SSH and JTAG.
Capstone project
Produce a synchronized multi-camera capture set with verified frame identity and a measured, bounded inter-camera skew distribution — delivered with the trigger topology map, the drift data behind the bound, and the operational checks that will detect sync loss after deployment.
What you leave with
- Trigger-distribution designs for 2–8 cameras with known skew floors
- A skew/drift measurement method you can run on your own rig
- Bandwidth budgeting across shared CSI receivers and aggregators
- Frame-identity validation tooling that catches drops and swaps
- Field checks that detect sync loss before the application silently degrades
How it runs
Every course follows the same model: 35% principles, 20% guided investigation, 45% engineering studio. You leave with working code, raw measurements and an evidence-based report — not a certificate of attendance. Read the methodology or see a full sample lesson.
Material is adapted to your kernel version, hardware and workload before a private delivery. For public cohorts, the environment is provided and configured.
Questions
Who is this course for?
System engineers building multi-camera rigs — surround view, stereo pairs, robotics arrays — whose cameras must agree on time tightly enough for fusion to work. It sits at advanced level within the Embedded Vision track.
What do I need to know already?
Specific prerequisites for this course: Camera pipeline basics (VIS-110 or equivalent capture experience); Basic timing electronics: oscillators, trigger signals, signal integrity awareness; Python or equivalent for timestamp analysis and plotting. We confirm levels before the cohort starts and adapt if a group is stronger or weaker than expected.
Can this run privately for my team?
Yes. Any course runs on-site at your offices anywhere, or live online for a distributed team, with labs adapted to your hardware and codebase.
What is the difference between in-person and online?
In person is 3 full days with hardware on your desk, capped at 14. Online is 6 half-day sessions across about two weeks so you can keep working, capped at 20, with remote lab access.
Do you invoice companies?
Yes. Purchase orders are accepted and invoicing is available in USD, EUR, GBP, SAR and CAD.
Upcoming dates
| Dates | Where | Seats | Early bird | Regular | |
|---|---|---|---|---|---|
| 18 Oct – 20 Oct 20263 full days | RiyadhIn person · KAFD Conference Centre | 9 of 14 | — | SAR 9,000 | |
| 25 Oct – 27 Oct 20263 full days | Kuwait CityIn person · Al Hamra Tower | 4 of 14 | — | KWD 740 | |
| 1 Nov – 3 Nov 20263 full days | MuscatIn person · Knowledge Oasis Muscat | 9 of 14 | — | OMR 920 | |
| 1 Nov – 8 Nov 20266 half-days | Gulf bandLive online · 09:00–13:00 GMT+3 | 5 of 20 | — | US$1,750 | |
| 2 Nov – 4 Nov 20263 full days | OttawaIn person · Kanata North Tech Park | 4 of 14 | — | CAD 3,260 | |
| 9 Nov – 11 Nov 20263 full days | TorontoIn person · MaRS Discovery District | 9 of 14 | CAD 2,930until 10 Oct | ||
| 9 Nov – 16 Nov 20266 half-days | Europe bandLive online · 09:00–13:00 CET | 10 of 20 | US$1,580until 10 Oct | ||
| 9 Nov – 16 Nov 20266 half-days | Americas bandLive online · 13:00–17:00 ET | 15 of 20 | US$1,580until 10 Oct | ||
| 16 Nov – 18 Nov 20263 full days | LondonIn person · Shoreditch Works | 4 of 14 | GBP 1,680until 17 Oct | ||
| 16 Nov – 18 Nov 20263 full days | BerlinIn person · Factory Görlitzer Park | 9 of 14 | EUR 1,990until 17 Oct |
Dates shown for the next few months. If nothing fits, tell us where and when — cohorts are added on demand, and private delivery can be scheduled any week.
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