AIThis post was created with the assistance of artificial intelligence (AI).
Corvus ISR tracker benchmark matrix (seed 1337)
The published matrix — every row reproducible. Source: corvusisr.com/benchmark

CORVUS ISR is a wide-area motion imagery (WAMI) exploitation product built entirely as a synthetic demonstration. Every pixel is generated: no real persons, vehicles, or places appear anywhere in the product.

Buying for a business?Offer from Amazon

Get business pricing on tech for your team

  • Business-only prices and quantity discounts
  • Tax-exempt purchasing
  • Multiple users, one account, clear invoices
As an affiliate, we earn on qualifying purchases.

Multi-object tracking is about preserving an object’s assigned identity across successive frames, making identity switches a critical measure of tracker performance. CORVUS ISR published the public benchmark using an identical fixed-seed synthetic scene with perfect ground truth: seed 1337, a 20s warm-up, and 120s measured per row. The sensor model, detection generation, and metric definitions are byte-identical; only the tracker differs.

The v1 model, “greedy nearest-neighbour,” is the deliberately simple baseline and published floor: two-pass greedy association, constant-velocity prediction, and fixed 2s coasting. It remains runnable in archived demo slices 1-2. The current v2 model, “confirmed-track auction,” appears in demo slice 3 and adds track confirmation, three-tier auction association, velocity-consistency gating, a noise-scaled reservation price, and confidence-decayed coasting.

In the baseline configuration of 150 movers at 2fps, ID switches per minute fell from 2,042 to 1,183, a 42.1% reduction. In the dense configuration with 400 movers, they fell from 14,032 to 8,040, a 42.7% reduction.

Corvus ISR live demo
The live demo — press “Run benchmark” to reproduce the numbers. Source: corvusisr.com/demo

The gains remained measurable under other stresses: 16.6% fewer switches in the frame-starved 0.5fps row, 18.6% fewer with 20% occlusion, and 18.1% fewer in the degraded 1fps + jitter, 70% contrast row. Detection rate is a sensor property and is identical for both models by construction.

The benchmark uses a deliberately stricter metric than the MOT-challenge IDSW definition, counting every change of the track identity assigned to a ground-truth object. Fragmentations and re-acquisitions count as switches too. Both models still commit thousands of identity errors per minute under stress, and CORVUS ISR publishes those rows on its own site because synthetic scenes provide perfect ground truth, making these measurements rather than marketing.

At a density of 400, v2 averages ~1.2ms per sensor tick, with a worst result of ~5ms against a 10ms budget, delivering real-time performance in the browser. The tracker was built by an AI executor against a written acceptance contract and independently reviewed before shipping.

The publication principle is explicit: “Vendors who show only successes ask for faith; a published failure matrix asks for measurement.” Every future tracker must land as a new public row against the same seed, and every current row can be run without signup or an NDA. Open the demo, press “Run benchmark,” and reproduce it live to run the benchmark yourself.

Powered by Thorsten Meyer AI


Amazon

multi-object tracking software

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Amazon

wide-area motion imagery (WAMI) surveillance system

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Amazon

real-time object tracker

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

Amazon

synthetic scene analysis tool

As an affiliate, we earn on qualifying purchases.

As an affiliate, we earn on qualifying purchases.

HALLOWEEN

Halloween Picks

As an affiliate, we earn on qualifying purchases.

You May Also Like

Algorithms Are Learning How to Manipulate Human Desire

What if algorithms are secretly learning how to manipulate your desires, and understanding their tactics could change how you see your choices?

Sony Accuses Anthropic Of ‘Brazen Campaign’ To Train Claude On Its Music — And Wants Up To $150,000 A Song – Business Insider

Sony accuses Anthropic of improperly using its music to train Claude and is seeking damages of up to $150,000 for each song at issue.

China’s Big Tech Wages ‘No Salary Cap’ Hiring War For Elite University AI PhDs – BigGo Finance

A headline describes Chinese tech firms competing for elite AI PhDs with uncapped pay, but provides no article details to verify the claim.

ByteDance Founder Tells AI Team To Stop Distilling Rival Models – Technology Org

ByteDance’s founder reportedly told its AI team to stop distilling rival models, but the order’s scope, timing and impact remain unclear.