Subpixel-Precise Tracking of Rigid Objects in Real-time
원문 초록
We present a novel object tracking scheme that can track rigid objects in real time. The approach uses subpixel-precise image edges to track objects with high accuracy. It can determine the object position, scale, and rotation with subpixel-precision at around 80fps. The tracker returns a reliable score for each frame and is capable of self diagnosing a tracking failure. Furthermore, the choice of the similarity measure makes the approach inherently robust against occlusion, clutter, and nonlinear illumination changes. We evaluate the method on sequences from rigid objects from the OTB-2015 and VOT2016 dataset and discuss its performance. The evaluation shows that the tracker is more accurate than state-of-the-art real-time trackers while being equally robust.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Car Object Counting and Position Estimation via Extension of the CLIP-EBC Framework
RGBTrack: Fast, Robust Depth-Free 6D Pose Estimation and Tracking
ReaMOT: A Benchmark and Framework for Reasoning-based Multi-Object Tracking
EOTNet: Deep Memory Aided Bayesian Filter for Extended Object Tracking
USVTrack: USV-Based 4D Radar-Camera Tracking Dataset for Autonomous Driving in Inland Waterways
SAM2Auto: Auto Annotation Using FLASH
토론
이 논문과 연결된 포럼 글이 아직 없습니다.