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Motion Capture Facility






About

A motion capture system, often referred to as MoCap, is a cutting-edge technology designed to track and record the precise 3D positions of several reflective markers attached to a subject. This system leverages specialized cameras and software to capture movements in real-time, enabling highly accurate motion tracking. MoCap has a broad range of applications, spanning multiple industries. In entertainment, it is widely used for creating lifelike animations in movies and video games. In healthcare, it supports gesture analysis, physical therapy, and rehabilitation by studying body movements. In sports, it aids in performance analysis and injury prevention by providing biomechanical insights. One of the leading providers in this field is Optitrack, an industry pioneer known for its high-quality motion capture and 3D tracking solutions. Their products are designed to meet the demands of both professionals and researchers. For facial motion capture, Optitrack offers a specialized system that consists of seven Flex IR cameras, combined with the Arena software. This software seamlessly integrates with the hardware, enabling precise tracking of facial expressions and movements. The process involves attaching reflective markers to key positions on the subject's face. These markers can be placed based on custom configurations or pre-defined templates provided by Optitrack. The system then tracks the 3D coordinates (x, y, and z) of each marker at an impressive speed of 120 frames per second, ensuring smooth and detailed motion capture. This level of accuracy is essential for applications such as creating realistic character animations, conducting advanced biomechanical studies, and even enabling real-time avatar interactions in virtual reality environments.

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Illustration of the recorded data by the Motion Capture Setup







Publications

Journals (Accepted and/or Published):

  1. C.A.Valliappan, Anurag Das, Prasanta Kumar Ghosh, "Classification of story-telling and poem recitation using head gesture of the talker", SPCOM 2018 [PDF]
  2. Gaurav Fotedar, Prasanta Kumar Ghosh, "An Information theoritic analysis of the temporal synchrony between head gestures and prosodic patterns in spontaneous speech", Interspeech 2017 [PDF]
  3. Sanjeev Kadagathur Vadiraj, Achuth Rao M V, Prasanta Kumar Ghosh, "Automatic Identification of Speaker from head gestures in a narration", ICASSP 2020 [PDF]
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