Egocentric Veneer Lamination and Pressing Data

Egocentric veneer lamination and pressing data is first-person video of a person laminating veneer, recorded from the contributor’s own point of view with synchronized sensor streams alongside. The camera sits on the head, close to what a robot’s onboard camera would see while it handles a sheet over a substrate, so the frames show the hands on the sheet, the adhesive being spread and the sheet being laid and pressed, rather than a distant view of someone in a workshop. On this site it is a custom collection: you name the task, the materials and the setting, and capture is run to a written skill spec.

The data is human capture. A paid, consented contributor wears the rig and does the task. It is not robot or teleoperation data, and it is not a fixed corpus you download. This page is a different subject from egocentric woodworking and carpentry data, which covers cutting, shaping, joining and finishing wood across eleven workshop rows, from adhesive and sealant application data, which centres on dispensing beads, caulk and glue-joint work, and from furniture restoration data, which centres on stripping, repairing and refinishing an existing piece. The subject here is the single catalog row that lays new veneer.

People reach this topic through close cousins: veneer lamination robot training data, a wood veneer pressing video dataset, egocentric glue-up and panel pressing data, or custom woodworking data collection. They describe one request from different angles, and the work is the same: write down the task, collect it on demand, and receive validated episodes. Nothing on this page states that the video carries a veneer-species label, a glue-line measurement or a pressure reading.

A published robot foundation model paper, GR00T N1, linked in the sources below, describes a data pyramid with web data and human video at the base, synthetic data in the middle and real robot trajectories at the top. First-person human video of veneer work sits in that base layer. Human capture does not replace robot data, and this page does not claim that it does.

Veneer lamination is a sequence of ordered moves with a thin, easily shifted workpiece. The catalog describes the row as cutting veneer sheets, spreading adhesive, positioning them on the substrate and pressing them flat. The order matters, and so do the hands: the site’s tool use page says that grip changes live in finger-level detail that RGB video alone cannot resolve. A clip that shows a sheet somewhere near a panel does not carry what a policy needs. The hands, the sheet and the substrate have to be present in the episode, and the episode has to say where one step ends and the next begins.

Breadth matters as much as volume. A published model write-up, GEN-0, also linked in the sources, puts it this way: "data quality and diversity matters more than sheer volume." For veneer work that points at the spread of sheets, substrates and steps. A custom collection lets you aim at the step your model is missing, such as positioning the sheet or pressing it flat, rather than hoping a broad collection happens to contain it. This page does not claim that any public corpus lacks veneer data.

The site’s commercial task catalog lists one row for this subject. "Veneer Lamination & Pressing" sits in the Carpentry & Furniture Workshop environment, which the catalog describes as a joinery and furniture workshop with saws, sanders and finishing stations. Its description reads "Cut veneer sheets, spread adhesive, position them on the substrate and press them flat." It is listed as hard, captured with a head-mounted phone or multiview rig, and marked ready to deploy. The first table below reproduces the row exactly as the catalog states it.

Two other catalog rows mention veneer, and they are separate listings. "Marquetry", in the Woodcraft & Carving Studio, cuts veneer pieces to pattern and glues them into a decorative inlay on a panel, and is listed as hard and available on request. "Furniture restoration", in the Repair Shop environment, strips old finish, repairs joints and veneer, sands and refinishes the piece, and is also listed as hard and available on request. The restoration row repairs existing veneer, so it does not count as lamination, and this page does not claim either row. The second table below sets the three side by side.

The site does not describe a veneer species, a sheet thickness, a substrate material, an adhesive type, a cutting tool, a press or a clamping method for the row, so none is stated here. A task outside the row is settled in a Spec Pilot rather than assumed.

Each attempt is delivered as one episode, and a veneer task needs a decision up front about what one attempt is: one sheet laid and pressed, one panel, one step such as spreading the adhesive, or one cut-to-press sequence. The site does not set that length, so the skill spec does. Inside the episode, the synchronized streams run from start to end, and action segments divide it into labeled spans.

An episode might open with the first veneer sheet being cut and close with the sheet pressed flat, as the catalog row words the sequence. That is an illustration of how a spec can cut an episode, not a stated duration. Whether the press is inside the episode or its own, and whether each sheet is one episode or several, are spec decisions.

The environment behind the row is the carpentry and furniture workshop. How many sheets, substrates and steps you want covered is set in the spec. The site lists capture at your own facility as not offered.

A veneer collection uses the same capture stack as every Firsthand program. The instrumented tier is a head-mounted stereo rig that records first-person RGB, with a metric depth stream recovered from the calibrated stereo rig rather than from a standalone depth sensor, and 6-DoF IMU data at 200 Hz from head- and wrist-mounted sensors. The wider stack is ten streams: a 4K head camera, two wrist cameras, depth, IMU, 3D hand and body pose, instance segmentation and action labels, hardware-aligned under 2 ms. The two wrist cameras give a closer view of the hands than the head camera alone, which matters where a hand smooths or steadies a sheet.

Every stream is hardware-triggered onto one PTP clock domain, so depth, motion and hand pose line up with the same video frame rather than being approximated afterwards. The rig is calibrated twice per session, before capture starts and after it ends, and an episode is accepted only if RMS reprojection stays under 0.28 px. The catalog lists a head-mounted phone or multiview rig for this row. Which tier applies to your program is set in the skill spec.

The site does not state a camera count, resolution or frame rate specific to veneer work. Force and tactile readings are not among the streams, and no robot or teleoperation data is captured.

Inside each episode, action segments divide the recording into start- and end-timestamped spans, each carrying start_ns, end_ns, verb and noun. For this task a segment can be one step as written in the skill spec, so the catalog row becomes a run of labeled steps such as cut, spread, position and press rather than one long clip. The other standard fields are hand_joints and hand_visible for 3D hand pose, contact_events for the moment the hand meets an object, objects, and instance_masks, stored at the depth resolution of 848×480 so they line up with the depth stream.

Hand pose is delivered for both hands with a per-joint visibility flag for occluded fingers. That is the label that carries how the hands sit on a sheet and how they move while it is laid down. The site describes contact events as the moment the hand meets an item, and it does not say whether a veneer sheet, the substrate or a press counts as the item, so the spec is the place to settle what a contact event means for your task.

The site does not list labels for the veneer or the glue-up itself. There is no stated label for veneer species, sheet or substrate dimensions, adhesive coverage, bond quality, alignment tolerance, flatness, or a task-completion score, and no contact force or pressure reading. The catalog description describes the task the contributor performs, not a delivered measurement.

Several limits the site already states apply directly to veneer capture, and several it leaves open. Each stated limit below appears elsewhere on the site rather than being introduced here.

Hand occlusion is the first. Fingers disappear behind objects in manipulation, which is why 3D hand pose carries a per-joint visibility flag. Depth is the second. The site says depth degrades on wet and reflective surfaces and handles that with per-frame confidence maps. A freshly spread adhesive surface may be wet, but the site does not say how depth behaves on one in particular, and it says nothing about thin sheets lying flat against a substrate.

The third is the set of machine-checked reject criteria. An episode is rejected for a sync breach beyond the ceiling for more than three consecutive frames, calibration drift beyond tolerance, the manipulated object out of frame for more than 15 percent of the episode, more than 35 percent invalid depth pixels in the manipulation region, an undocumented bystander, or a mismatch against the named skill spec. A human reviewer then checks each episode against the task spec. For a veneer task, the spec decides what the manipulated object is: the sheet, the substrate or the pressed panel.

Also not stated: a mask accuracy figure for veneer sheets or substrates, and any description of how a sheet held flat under a press, or hidden beneath one, is handled. If your policy depends on any of those, say so at the start.

Validation runs against signed accept criteria written into the spec before capture. Each batch goes through per-batch QA and a reject log ships with it. Only footage that clears the criteria is billed as a validated hour, and rejected items are recaptured at our cost. Many teams start with a Spec Pilot, a small, fast first batch that proves the spec and the accept criteria on real footage before volume scales.

Every contributor signs a written release before capture, and each delivered episode links to that record through consent artefact IDs in the batch data card. The consent chain has six checkpoints, from before capture to after delivery, and a break at any one discards the footage rather than shipping it at a lower grade. At ingest, automated detection finds faces, plates and screens and blurs them irreversibly, and speech is scrubbed of names, addresses and card numbers while ambient audio is kept. A human reviewer confirms that no un-consented person is identifiable in any frame, and footage that cannot be de-identified is discarded. The anonymization record is delivered with the data.

Workshops can have other people nearby. The same rule applies to them as to any capture: an un-consented person who is identifiable in a frame means the footage is de-identified or discarded, so settle bystander handling in the spec.

On safety and qualification, the site states no contributor safety protocol, no guidance on adhesive handling, ventilation or protective equipment, no adhesive-chemistry, cure-time or press-pressure information, and no safety or trade certification for the veneer row, and this page does not describe one. The site lists capture at your own facility as not offered. If your program needs terms about who performs the work, the materials used or the conditions under which it is done, raise them when you scope it. None of this is legal advice, and the executed agreement controls.

From signed spec to first validated batch, the timeline is a median of 48 hours where coverage is deep and three to four weeks where it is thin and contributors need to be recruited first. Speed comes from a warm pipeline, not from cutting consent, review or anonymization. The veneer row is marked ready to deploy, but the site does not say whether the carpentry workshop counts as deep or thin coverage, so ask which timeline applies when you request the quote. After the first batch, on-demand top-ups run against the same accept criteria, so you can add more sheets, substrates or steps without rewriting the spec. The site does not state a turnaround for those later batches, so plan them in your quote.

Delivery is in the format your stack already reads: RLDS, LeRobot, WebDataset, HDF5, zarr or Rerun .rrd, or raw streams with metadata. Readable converter source ships alongside the data so the schema can be retargeted to your own loader. Collections are billed per validated hour.

The license is perpetual, irrevocable and worldwide, with the data buyer-owned and non-exclusive by default. Training, evaluating, fine-tuning and deploying models, including commercial ones, is permitted, and exclusivity is available as a separate term. The executed agreement controls. The site does not publish a price list, a minimum order or a batch size for this task, so those are set in your quote.

Where this site does not state something, this page says "not stated" rather than filling the gap. The table below separates what is delivered from what is not stated. There is no listed label for veneer species, thickness, adhesive coverage, bond quality or flatness, no force or tactile stream, no tool, press or adhesive specification, and no claim about cure time or press pressure. Nothing here claims a training outcome or a model improvement.

The tradeoff to plan for is the embodiment gap between a human hand laying and smoothing a thin sheet and a robot platform doing the same, which retargeting or pairing with robot data has to close. Counts of contributors, hours and sheets are set in your skill spec.

Describe the sheets, the substrates, the setting and the variation or failure cases your pipeline is missing. That becomes a written skill spec, quoted for reach, timeline and price before any capture begins, and most programs run a Spec Pilot first. The scoping checklist below maps the parts of a skill spec onto a veneer request. A published sample recording is on the sample data outputs page if you want to see the streams before you write a spec.

Three choices matter most for this task. Name each step rather than a broad activity, because that is what lets each step become one action segment. Name the setting and the capture tier, since the catalog lists a head-mounted phone or multiview rig for the row. And name where the episode starts and stops: one sheet, one panel or one full cut-to-press sequence, since the site does not set an episode length.