# Non-Causal Tracking by Deblatting Source: [Non-Causal Tracking by Deblatting]() Collection index: [llms.txt]() Data updated: 2025-10-25T21:57:21.263Z Authors: Denys Rozumnyi, Jan Kotera, Filip \\v{S}roubek, Ji\\v{r}\\'i Matas Published: 2019-09-15T22:02:43.000Z ## Abstract Tracking by Deblatting stands for solving an inverse problem of deblurring and image matting for tracking motion-blurred objects. We propose non-causal Tracking by Deblatting which estimates continuous, complete and accurate object trajectories. Energy minimization by dynamic programming is used to detect abrupt changes of motion, called bounces. High-order polynomials are fitted to segments, which are parts of the trajectory separated by bounces. The output is a continuous trajectory function which assigns location for every real-valued time stamp from zero to the number of frames. Additionally, we show that from the trajectory function precise physical calculations are possible, such as radius, gravity or sub-frame object velocity. Velocity estimation is compared to the high-speed camera measurements and radars. Results show high performance of the proposed method in terms of Trajectory-IoU, recall and velocity estimation. ## Recorded benchmark results A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage. - [3D Object Location and Pose Estimation on TbD-3D 1.0 (Average)](): 3D Object Location and Pose Estimation; TbD-3D 1.0 (Average); TIoU-3D: 50. ## Original sources and implementation [Original paper]() [PDF]()