We execute targeted field data capture campaigns across India to power spatial computing, bimanual robotics manipulation, and computer vision models. Double-opt-in consent logs, 7-14 day mobilisation, and full GDPR compliance.
A real-time snapshot of active first-person (egocentric) POV and robotics training data collection drives across India.
Active
Continuous first-person video capture of manual labor workflows in textile and garment manufacturing units. Utilizing high-resolution head-mounted cameras to record fine-grained hand-object manipulation, tool usage, and sewing machine operations in natural factory settings.
Active
High-fidelity dataset capturing driver and operator attentiveness using head-mounted eye-tracking rigs. Simultaneously records dual-eye infrared gaze vectors and external scene views, training attention-mapping and safety-critical ML models for autonomous transport.
Active
Rigorous bimanual manipulation data capturing hand poses, finger joint tracking, and object grip configurations. Subjects wear sensor-equipped smart gloves and wrist-tracking modules during multi-step sorting, folding, and assembly tasks, feeding training loops for next-generation humanoid hands.
Active
First-person camera datasets of common domestic tasks and smart appliance operations. Features egocentric video recording of cooking, cleaning, and meal preparation under varying indoor lighting conditions. Designed to train home-assistant robotics.
No synthetic data, no web-scraping — every dataset is captured by trained field operatives from real consented participants under rigorous QA audits.
Chest rigs, head mounts, and eyewear capturing commutes, manual labor, and domestic tasks—the exact visual coordinates your robotics models require to learn.
Subjects walking, cooking, shopping, driving, and interacting across urban, semi-urban, and rural Indian environments. Visual complexity at scale.
Fine-grained hand-object interactions, bimanual sorting, and tool usage across textile units, agricultural fields, and warehousing operations.
Skeletal keypoint landmarks, bounding boxes, polygon segmentation, temporal boundary tags, and frame metadata mapping.
Multi-camera capturing of gestures, micro-expressions, and physical trajectories across diverse age, gender, and regional demographics.
Acoustic data recorded in natural settings (home, street, work) across 10 major Indian languages to close the ASR accent gap.