Stereo Hotel Room Turnover and Housekeeping Data

It is first-person video of a person working in a hotel guest room: stripping and making beds, cleaning bathrooms, dusting, vacuuming, restocking, resetting the room after checkout, checking items against the standard and reporting faults. It is recorded from their own point of view with two calibrated cameras, with hand pose and sensor streams alongside. The tasks are the rows the site’s catalog lists for it. Stereo describes the capture, and MCAP describes the container. They are separate choices.

The site does not state that stereo is already running on these rows. The catalog lists a head-mounted phone or a multiview rig as the capture setup, and a stereo pair is a capture choice agreed in the skill spec and confirmed on a Spec Pilot. The data is human capture by paid, consented contributors, not robot or teleoperation data. Firsthand is not affiliated with Foxglove or the MCAP maintainers.

Four, all in the Hotel & Lodging environment of the Hospitality & Events sector. The first is "Room Turnover & Inspection", rated Medium: "Reset the room after checkout, check every item against the standard and report faults." The second is "Hospitality Housekeeping", rated Easy: "Strip and make beds, clean bathrooms, dust and vacuum and restock guest rooms." The third is "Hotel Bed Making", rated Easy: "Fit sheets, tuck corners, place the duvet and arrange pillows to hotel standard." The fourth is named "Vacuum and dust guest rooms using a vacuum cleaner and microfiber cloths", rated Easy: "Vacuum carpets and dust surfaces in the guest room with a vacuum and microfiber cloths."

All four list a head-mounted phone or a multiview rig as the capture setup, and all four are Ready to deploy. The site says nothing further about what that status means in volume, hours or delivered stereo footage, so this page claims none, and what applies to a given order is confirmed when you request the quote. This page names only the tools and steps that appear in the rows: beds and bed linen, bathrooms, dusting, vacuuming, restocking, a vacuum cleaner and microfiber cloths, the standard and faults. The first table below reproduces the four rows as the catalog states them. Other rows in the same environment, such as bathroom cleaning and amenity restocking, are covered on the egocentric hotel room turnover page.

The egocentric hotel room turnover page treats the room reset as egocentric capture across a wider set of hotel rows and the hospitality service set, with the full stream and label picture. The stereo floor mopping page treats nine mopping, floor-care and janitorial rows as stereo and MCAP work; its rows are cleaning rows in other environments, plus one lobby row in Hotel & Lodging, and guest room turnover is not its subject.

This page narrows to the four guest room rows named above and gives them their own stereo and MCAP treatment, stream map and failure modes. The site lists no off-the-shelf hotel room turnover or housekeeping dataset, so this work is custom collection. The comparison table below sets the pages side by side.

A room reset is mostly soft, changing objects: sheets, a duvet, pillows, cloths. A stereo pair recovers depth from the calibrated frame pair rather than from a standalone depth sensor, so the bed, the surfaces and the hands share a frame. The site also states that depth degrades on wet and reflective surfaces and handles that with per-frame confidence maps.

The site gives no depth accuracy figure and no label for how a sheet is laid, whether a corner is tucked, how clean a surface is or whether an item meets the standard, so whether those are resolvable in depth is Not stated. How stereo depth behaves on white linen, mirrors or wet bathroom fixtures is Not stated, and a spec should check it on a Spec Pilot. Capture at your own facility is listed as not offered.

The site describes two stereo setups and does not say which one a room turnover order uses. The hard-environments stack is a global-shutter 4K/60 head camera with a 120° lens, two 1080p/60 wrist cameras, a depth sensor at 848×480 and 30 fps, and 200 Hz 6-DoF IMUs. The off-the-shelf stereo head rig, dataset 06, is dual fisheye cameras at 1080p per eye, a 62 mm baseline, per-unit calibration, a 9-axis IMU and hand-tracking output.

Which rig, resolution and streams a room turnover order uses is Not stated on the site, and the third table below sets what is stated beside what is not. Intrinsics and extrinsics are re-solved at the start and end of every session, and streams are hardware-triggered onto one clock with a 2.0 ms cross-stream ceiling. The catalog states that a multiview rig adds synchronized third-person angles when the spec asks for them, and wrist cameras give a closer view of the hands, which matters when one hand holds linen and the other tucks or smooths it.

MCAP is an open source container file format for multimodal log data, supporting multiple channels of timestamped pre-serialized data. It is serialization-agnostic, so messages can be Protobuf, DDS (CDR), ROS, JSON and more. Its design is row-oriented and append-only, it stores schemas alongside the data, and it offers an optional index plus optional LZ4 or Zstandard chunk compression.

Reader and writer libraries exist for C++, Go, Python, Rust, Swift and TypeScript, and the mcap CLI can inspect, merge and split files. The foxglove/mcap repository is MIT-licensed; that is the MCAP project’s licence, not the licence of a Firsthand delivery. The MCAP hub page and the glossary entry cover the format in full.

Firsthand offers MCAP delivery, and dataset 06 is stated as shipping as MCAP. For room work the site states hand pose, a stereo-derived depth stream with confidence maps, IMU, contact events, action segments and per-frame instance masks elsewhere. What it does not state is which of those are channels in an MCAP file, how they are named, what encoding they use or at what rate.

No topic name, message schema or rate is stated on this page, and none should be assumed. Name the streams that matter in the skill spec and confirm them on a Spec Pilot batch. The fourth table below sets each stream beside what the site states about it.

Occlusion is the first risk. A sheet, a duvet or a cloth can hide the fingers that hold it, and the item being worked changes as the contributor turns between the bed, the bathroom and the floor. The visibility flag on each joint is the answer the site gives, contact events mark when a hand meets an item, masks are recorded per frame, and a spec can ask for wrist views so a grip the head camera loses is still recorded.

Sequence and definition are the second. The turnover row names three actions, reset, check against the standard and report faults, and the site defines neither the standard nor how a fault is reported. The spec decides how each step is split into action segments and whether the check and the report sit inside the episode. A spec that says only “turn the room” gives one long segment. Chemicals, cleaning times, room counts and inspection checklists are Not stated and are raised in the spec. Force and tactile readings are not among the listed streams of standard capture.

Calibration is the third, because stereo depth is only as good as the rectification behind it: calibration is measured at the start and end of every session under a 0.28 px RMS gate. An episode is also rejected when the manipulated object is out of frame for more than 15 percent of it, when more than 35 percent of depth pixels in the manipulation region are invalid, or when an undocumented bystander appears, and a reject log ships with every batch.

The site classes room turnover as back-of-house work and states that front-of-house settings are bystander-dense with lower yield after de-identification. Whether a room is occupied during capture, and how guests are handled, is Not stated, and this page makes no claim about either. An undocumented bystander is a stated reject criterion.

For every delivered episode the site states that faces, plates and screens are blurred irreversibly, and that footage that cannot be de-identified is discarded. The anonymization record ships with the data. Anything beyond that general rule is settled in the spec before capture.

The site lists no off-the-shelf hotel room turnover or housekeeping dataset. Hotels appear in the off-the-shelf catalog only as an industry in the 360° virtual tour category, which is panoramic imagery, not task video. The only stereo head rig the site states as shipping as MCAP is dataset 06, and this page does not claim off-the-shelf stereo coverage of room turnover. So this work is custom collection: custom collection at scale through a network of thousands of capture providers, for a consistent, recurring data flow to labs.

Where coverage is deep, the median time from signed spec to first validated batch is a median of 48 hours; where it is thin, turnaround runs three to four weeks. The site lists hospitality coverage as thin and does not say which speed applies to a stereo room turnover order, so the timeline is quoted against your spec. Collections are billed per validated hour, and rejected episodes and recaptures are never billed.

Describe the tasks and where each starts and ends: the bed, the bathroom, the dusting and vacuuming, the restock, the check against the standard and whether the fault report is inside the episode, the start state of the room, what counts as a reject, and the variation your pipeline is missing. Then name the streams you want in the file, the topic naming and message encoding your reader expects, whether calibration ships inside the file or beside it, and whether MCAP is the only delivery or sits beside RLDS, LeRobot or WebDataset.

Most programs begin with a Spec Pilot, a small first batch that proves the spec and accept criteria on real footage before you scale. The fifth table below shows what each spec element decides.