Non-Causal Tracking by Deblatting
원문 초록
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.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Generative Latent Kernel Modeling for Blind Motion Deblurring
EAMamba: Efficient All-Around Vision State Space Model for Image Restoration
Visual-Instructed Degradation Diffusion for All-in-One Image Restoration
R3eVision: A Survey on Robust Rendering, Restoration, and Enhancement for 3D Low-Level Vision
Unsupervised Imaging Inverse Problems with Diffusion Distribution Matching
Plug-and-Play Linear Attention for Pre-trained Image and Video Restoration Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.