Two-Wheeler Video Analytics for Motorcycles and Bikes

A motorcycle is not a small car. It carries a plate a fraction of the size, one or two riders who may or may not wear helmets, and it goes where cars cannot: pavements, pedestrian zones, bus lanes, bike lanes. IREX treats two-wheelers as their own class, with their own detectors and their own rules.

The Class

Their Own Class Since Release 4.36

Most traffic models learned two-wheelers as an afterthought, so a motorcycle in mixed traffic came out as a small car or as nothing at all. In release 4.36 IREX retrained CarTrack Pro to recognize two-wheelers as a class of their own, count the riders, and detect whether helmets are worn. Release 4.37 extended that classification across the full set of tracking modes, and 4.39 improved rider counting and helmet detection, including when a rider is only partially visible in the frame. The class is broad on purpose: any two- or three-wheeled motorized vehicle, including tricycles, scooters and mopeds.

The read is one pass. A first network finds the vehicle, a second reads its type and color and, for a motorcycle, the riders and their protective gear, and a third and fourth find and read the plate. One read therefore returns the vehicle class, the plate, the rider count and the helmet status together, which is what a multi-rider or no-helmet rule is written against and what an investigator filters the archive on afterwards.

Bicycles are a separate problem and a separate module. BikeLaneTrack watches a bike lane for what should not be in it; the network behind it recognizes humans, bikes, cars, dogs and other object types, and treats a bike with a rider close enough to it as one cyclist. Where the trained catalog stops, StreamVLM™ continues: a motorbike on the sidewalk and a two-rider robbery pattern are both prompts already running on our own home page. StreamVLM is shipping in beta on selected instances.

Coverage

Six Things It Does on Two Wheels

Detection, Classification and Tracking

Motorcycles, scooters, mopeds and tricycles as their own vehicle class in every CarTrack Pro tracking mode, followed across the frame and, with Save tracks on, searchable by trajectory in the media player afterwards.

Small and Specialized Plates

A motorcycle plate is a fraction of the area of a car plate and is often two-line or non-Latin. A regional plate model is selected per camera, a minimum plate size stops the platform guessing, and since 4.39 a missing or unreadable plate raises its own event.

See License Plate Recognition

Rider Count

How many people are on the motorcycle, read on the same pass as the plate. More than one rider is the pattern a multi-rider rule is written against, and the Motorcyclists filter returns those events on their own.

Helmet Detection

Whether each rider is wearing a protective helmet, recorded as an attribute of the event. Improved in 4.39 for riders only partly visible in the frame.

Two-Wheelers Where They Are Banned

Motorcycles in car-only or bus-only lanes, in pedestrian zones, on crossings, or entering tunnels and highways closed to them, captured as a lane-restriction or forbidden-maneuver violation with the vehicle type as the rule.

Other Vehicles in the Bike Lane

BikeLaneTrack raises a Not a bike event for a pedestrian, a stroller or a skateboarder in the lane, and a lane-restriction rule catches a car or a truck using it as a road.

On Camera

Where a Two-Wheeler Goes, and Should Not

Motorbikes on the Sidewalk

Two small motorbikes ride the pavement under an elevated railway in Bangkok while pedestrians press against the shopfronts to let them pass. A car-shaped model misses this twice: it does not see the vehicle, and it has no rule for a pavement. Here the rule can be a lane-restriction area drawn over the pavement with Motorcycles as the prohibited type, an ObjectTrack Pro Region entrance rule filtered to vehicles, or a sentence typed into StreamVLM™, which is the detector this frame was written for. Whichever fires, the event carries the frame, the plate where it is legible, and the time.

Two small motorbikes ride one behind the other along a Bangkok pavement beneath an elevated railway viaduct, weaving around a concrete support pillar, while three pedestrians pressed against the shopfronts let them pass.
The prompt behind this frame demanded no legible plate, so none is asserted from it: the rule fires on the class and the place.

The Rules

Three Ways to Write a Two-Wheeler Rule

The class is the thing. Once a vehicle is read as a motorcycle, the platform’s existing enforcement machinery applies to it, and the operator chooses which mechanism fits the road.

  1. 01

    A Lane Restriction

    Draw a motion control area over the restricted lane, crossing or zone on a camera running CarTrack Pro with vehicle type recognition on, name the violation, and select the vehicle types prohibited there. Written with Motorcycles as the type, it is a motorbike in a bus lane; written with every motor class, it is a car in the bike lane. The evidence package is the one every traffic violation gets.

  2. 02

    A Forbidden Maneuver

    Entry and exit lines on a junction, with an optional vehicle-type filter, so a maneuver legal for a car can be a violation for a motorcycle, or the other way round. Exemptions by vehicle list or plate template let a permitted fleet through, which is how transit-priority rules already work.

  3. 03

    A Rider Rule

    Enable Count people on a motorcycle, detect safety gear in the CarTrack Pro settings, in any of the three tracking modes that support it. Every motorcycle read then carries its rider count and helmet status, searchable through the Motorcyclists filter, so more than one rider or no helmet becomes a query as well as an alert.

Camera

What the Camera Has to Give It

Two-wheeler detection is a pixels-per-meter question before it is a model question. The figures below are the documented CarTrack Pro and BikeLaneTrack ones.

Vehicle Detection
More than 25 pixels per meter inside the region of interest and a vehicle outline of at least 2,025 pixels, meaning 45 × 45; a mount 3 to 15 meters up with the camera tilt between +15° and +75°. Fixed or PTZ mount, 1280 × 720 to 2592 × 1944, 10 to 60 frames per second depending on vehicle speed.
Plate Reading
More than 250 pixels per meter, a plate image at least 80 pixels wide and preferably 125, a mount 2 to 6 meters up with the tilt inside 0° to +20°. On a motorcycle plate that means a closer camera or a longer lens than the same road needs for cars.
Bike Lanes
BikeLaneTrack wants the camera pan, tilt and roll each within 45° of the lane and a typical object size of 4,000 to 5,000 square pixels. The Bike and Not a bike events each take a priority, a similarity threshold and a minimum number of frames.
Compute and Sources
CarTrack Pro is rated High in computational complexity and runs on standard CPUs through the proprietary Synet framework, so servers are sized against camera count and module mix. Enforcement runs on fixed cameras; drone or uploaded footage supports vehicle recognition where the viewing angle is shallow.

FAQ

Does it read motorcycle plates?

Yes, and two-wheelers are their own vehicle class rather than a car that came out small. Motorcycle plates are a fraction of the area of a car plate, so the minimum plate size setting matters more here than anywhere: set the pixel width below which the platform should decline the read rather than guess. A regional plate model is selected per camera, and two-line plates and non-Latin scripts such as Thai are supported. Where the plate is missing or unreadable, the platform says so with its own event rather than inventing characters.

Can it tell how many people are on the bike?

Yes. Rider counting and helmet detection are part of the same CarTrack Pro read as the plate, enabled per camera with the Count people on a motorcycle, detect safety gear option in any of the three tracking modes that support it. Release 4.39 improved both, including when a rider is only partially visible. IREX publishes no accuracy figure for either; they are benchmarked on your cameras during the pilot.

Does helmet detection work on cyclists?

Helmet detection is documented for motorcycle riders, through CarTrack Pro. For bicycles the documented module is BikeLaneTrack, which watches a lane for a cyclist and for what should not be there. A separate safety-gear check exists in ObjectTrack Pro for people on foot at work sites. If cyclist helmet compliance is the requirement, raise it before the pilot rather than assuming it.

What counts as a two-wheeler?

The Motorcycles class covers any two- or three-wheeled motorized vehicle: motorcycles, tricycles, scooters and mopeds. Bicycles are handled separately by BikeLaneTrack, and skateboards, strollers and pedestrians in a bike lane are reported as Not a bike.

Can we get an alert when a motorbike enters a pedestrian zone?

Yes, and there are two documented ways to write it. A lane-restriction rule with Motorcycles as the prohibited type on a motion control area drawn over the zone, or an ObjectTrack Pro Region entrance rule filtered to vehicles. Where the zone is irregular or the condition is more specific, such as a motorbike on the sidewalk, a StreamVLM™ prompt does the same job (beta, selected instances).

Does it need a GPU?

No. CarTrack Pro runs on standard CPUs through the proprietary Synet framework, though it is rated High in computational complexity, so IREX engineering sizes the servers against camera count and module mix. StreamVLM™ prompts, where you use them, need a GPU node.

How accurate is it on our cameras?

That is the right question, and the honest answer is that we measure it rather than quote it. IREX does not publish per-module accuracy figures, because a number from another city’s cameras tells you very little about yours. Accuracy is benchmarked on your own feeds during the pilot, against two or three success criteria agreed in writing before it starts, and the measured numbers are what go into the contract.

What camera quality does it need?

Any camera that supports ONVIF or streams RTSP with H.264 or H.265 on a static IP can be connected, but connection is not the bar. Each module sets its own resolution, mount position, height, and angle-of-view requirements in the camera requirements, the flagship modules need higher-resolution imagery of the scene than a bare stream, and the recommended primary stream is 1920 × 1080 or 1920 × 1440. A site survey confirms every camera against the module it will run.

Does this run on its own or does someone have to watch it?

It runs on its own and alerts a person. Detections are signals for a human to verify: no response runs autonomously, and the verification and decision are logged against the same Case ID as the detection.

Bring the Junction with the Most Motorbikes

Two-wheeler analytics is a pixel-size question first. One camera on your busiest approach answers it faster than a specification sheet.