Projects per year
Dynamic environments that include unstructured moving objects pose a hard problem for Simultaneous Localization and Mapping (SLAM) performance. The motion of rigid objects can be typically tracked by exploiting their texture and geometric features. However, humans moving in the scene are often one of the most important, interactive targets – they are very hard to track and reconstruct robustly due to non-rigid shapes. In this work, we present a fast, learning-based human object detector to isolate the dynamic human objects and realise a real-time dense background reconstruction framework. We go further by estimating and reconstructing the human pose and shape. The final output environment maps not only provide the dense static backgrounds but also contain the dynamic human meshes and their trajectories. Our Dynamic SLAM system runs at around 26 frames per second (fps) on GPUs, while additionally turning on accurate human pose estimation can be executed at up to 10fps.
|Title of host publication||2021 IEEE/RSJ International Confence on Intelligent Robots and Systems|
|Publisher||Institute of Electrical and Electronics Engineers (IEEE)|
|Number of pages||8|
|Publication status||Published - 16 Dec 2021|
|Event||2021 IEEE/RSJ International Conference on Intelligent Robots and Systems - Online, Prague, Czech Republic|
Duration: 27 Sep 2021 → 1 Oct 2021
|Conference||2021 IEEE/RSJ International Conference on Intelligent Robots and Systems|
|Abbreviated title||IROS 2021|
|Period||27/09/21 → 1/10/21|
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- 1 Active
HARMONY: Enhancing Healthcare with Assistive Robotic Mobile Manipulation
Vijayakumar, S., Ivan, V., Khadem, M. & Li, Z.
1/01/21 → 30/06/24