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Sensors 2017, 17(10), 2342; https://doi.org/10.3390/s17102342

Model-Based Real-Time Non-Rigid Tracking

Electronics Department, University of Alcalá, Campus Universitario, 28805 Alcalá de Henares, Spain
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Received: 19 September 2017 / Revised: 29 September 2017 / Accepted: 10 October 2017 / Published: 14 October 2017
(This article belongs to the Special Issue State-of-the-Art Sensors Technology in Spain 2017)
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Abstract

This paper presents a sequential non-rigid reconstruction method that recovers the 3D shape and the camera pose of a deforming object from a video sequence and a previous shape model of the object. We take PTAM (Parallel Mapping and Tracking), a state-of-the-art sequential real-time SfM (Structure-from-Motion) engine, and we upgrade it to solve non-rigid reconstruction. Our method provides a good trade-off between processing time and reconstruction error without the need for specific processing hardware, such as GPUs. We improve the original PTAM matching by using descriptor-based features, as well as smoothness priors to better constrain the 3D error. This paper works with perspective projection and deals with outliers and missing data. We evaluate the tracking algorithm performance through different tests over several datasets of non-rigid deforming objects. Our method achieves state-of-the-art accuracy and can be used as a real-time method suitable for being embedded in portable devices. View Full-Text
Keywords: SfT; tracking; PTAM; non-rigid reconstruction; SfM; NRSfM SfT; tracking; PTAM; non-rigid reconstruction; SfM; NRSfM
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
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Bronte, S.; Bergasa, L.M.; Pizarro, D.; Barea, R. Model-Based Real-Time Non-Rigid Tracking. Sensors 2017, 17, 2342.

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