{"ID":2824879,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2512.22690","arxiv_id":"2512.22690","title":"Mesquite MoCap: Democratizing Real-Time Motion Capture with Affordable, Bodyworn IoT Sensors and WebXR SLAM","abstract":"Motion capture remains costly and complex to deploy, limiting use outside specialized laboratories. We present Mesquite, an open-source, low-cost inertial motion-capture system that combines a body-worn network of 15 IMU sensor nodes with a hip-worn Android smartphone for position tracking. A low-power wireless link streams quaternion orientations to a central USB dongle and a browser-based application for real-time visualization and recording. Built on modern web technologies -- WebGL for rendering, WebXR for SLAM, WebSerial and WebSockets for device and network I/O, and Progressive Web Apps for packaging -- the system runs cross-platform entirely in the browser. In benchmarks against a commercial optical system, Mesquite achieves mean joint-angle error of 2-5 degrees while operating at approximately 5% of the cost. The system sustains 30 frames per second with end-to-end latency under 15ms and a packet delivery rate of at least 99.7% in standard indoor environments. By leveraging IoT principles, edge processing, and a web-native stack, Mesquite lowers the barrier to motion capture for applications in entertainment, biomechanics, healthcare monitoring, human-computer interaction, and virtual reality. We release hardware designs, firmware, and software under an open-source license (GNU GPL).","short_abstract":"Motion capture remains costly and complex to deploy, limiting use outside specialized laboratories. We present Mesquite, an open-source, low-cost inertial motion-capture system that combines a body-worn network of 15 IMU sensor nodes with a hip-worn Android smartphone for position tracking. A low-power wireless link st...","url_abs":"https://arxiv.org/abs/2512.22690","url_pdf":"https://arxiv.org/pdf/2512.22690v2","authors":"[\"Poojan Vanani\",\"Darsh Patel\",\"Danyal Khorami\",\"Siva Munaganuru\",\"Pavan Reddy\",\"Varun Reddy\",\"Bhargav Raghunath\",\"Ishrat Lallmamode\",\"Romir Patel\",\"Assegid Kidané\",\"Tejaswi Gowda\"]","published":"2025-12-27T19:39:51Z","proceeding":"cs.MM","tasks":"[\"cs.MM\",\"cs.CV\"]","methods":"[]","has_code":false}