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Egocentric Video Data
First-person video from wearable cameras and smart devices, showing tasks as the person doing them sees them. For robotics and embodied AI.
POV recordingWearablesHuman activity
Collect / Annotate / Deliver
AI training data for the next generation of machines.
We collect and annotate egocentric, exocentric and multi-camera video, plus audio and image datasets, for robotics, computer vision and speech AI teams.
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What we do
We build the data that teaches machines to see, hear and understand. First-person and third-person video, synchronized multi-camera recordings, speech and images, labeled by expert annotators.
Explore services
Services
Everything your model needs to learn from.
Custom collection and labeling, planned around your task: the viewpoint, sensors, environments and annotations your model actually needs.
Get started02↗
Exocentric Video Data
Third-person video from CCTV, drone, vehicle-mounted and fixed cameras. For computer vision and spatial AI.
CCTVDroneCrowd & traffic
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Multi-Camera Recording
Synchronized, calibrated multi-view video of one scene, combining head, wrist, chest and scene cameras for 3D vision and activity understanding.
SynchronizedCalibrated rigs3D & pose
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Data Annotation
Expert labeling that turns raw footage into structured training data, checked in a QA review before delivery.
BoxesSegmentationTrackingActions
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Audio Data Collection
Multilingual speech recordings, voice commands, conversations and environmental sounds for voice AI and speech recognition.
SpeechCommandsSound events
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Image Data Collection
Multilingual image sets of signage, handwriting, infographics and shop fronts for computer vision and OCR.
HandwritingSignageInfographics
How it works
Start a project
From brief to delivered dataset.
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Scope the use case
You share the model goal, scenes, actions, languages and volume. We confirm the data type and setup that fit.
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Plan the capture
We choose cameras, microphones and locations, define scenarios, and set the labeling guidelines.
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Collect
Participants and equipment record in real environments, following the agreed protocol.
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Annotate
Annotators add boxes, masks, tracks, actions and events, with metadata structured for your pipeline.
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Quality review
Every batch is validated against the guidelines, and issues are fixed before delivery.
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Deliver & support
You receive the dataset in the format you asked for, with support for fixes and follow-up batches.
Built for teams working on robotics, embodied AI, spatial AI, 3D vision, human activity recognition, speech recognition and OCR.
FAQ
Questions, answered.
What is egocentric video data?
Egocentric video is recorded from a first-person point of view, usually with head-mounted or chest-mounted cameras. It shows what a person sees and does, which makes it valuable for training robots and embodied AI on real human activity.
What is the difference between egocentric and exocentric video?
Egocentric video comes from the actor's own viewpoint. Exocentric video is captured from outside the scene with CCTV, drones, vehicle-mounted or fixed cameras. Many projects use both so the model sees an action from the inside and the outside.
Do you support multi-camera and synchronized recording?
Yes. We record synchronized, calibrated multi-view video using combinations such as head-mounted, wrist-mounted and scene cameras, with extra sensor data where the project needs it.
Which annotation types do you provide?
Bounding boxes, object tracking, semantic and instance segmentation, action and event labeling, and human pose annotation. Each batch goes through a QA review before delivery.
Can you collect audio and image data in several languages?
Yes. Audio collection covers speech, voice commands, conversations and environmental sounds across languages. Image collection covers multilingual signage, handwriting, infographics and shop fronts.
How do I start a project?
Email hi@goodtimesol.com with your model goal, data type, volume and timeline. We reply with questions and a proposed collection and annotation plan.