Periodic Reporting for period 1 - SeerPredict (Analysis of skeletal kinematics for vision-based motion capturing)
Reporting period: 2020-10-01 to 2022-03-31
With SeerPredict we develop novel machine learning algorithms to improve the reliability and quality of the skeleton estimation and prediction resulting in substantial improvements to the talent tracking performance and overall autonomy of Seervision’s video production solution, making high-quality live video more accessible and affordable.
1) We have developed a novel software module that identifies person-to-person occlusions, especially during crossings, as they occur and mitigates their effect on the quality of the extracted skeleton, enhances the robustness and smoothness of the tracking.
2) We have re-designed the architecture of Seervision’s visual perception and tracking solution, incorporating recent advances in the computer vision research literature. This has reduced the delay that needs to be compensated with skeletal prediction, yielding state-of-the-art performance. In addition, it has also reduced the overall computational overhead.
The developed software has been extensively tested under laboratory conditions, during internal productions and demos at Seervision’s in-house studio and finally with selected customers who have seen a clear improvement in the quality and performance of the talent tracking.