Search Results for "tracker"

...Henriques, Andrea Vedaldi, and Philip H. S. Torr. The framework combines correlation filters with deep convolutional neural networks to create an efficient and accurate visual object tracker. Unlike traditional correlation filter trackers that rely on hand-crafted features, CFNet learns feature representations directly from data in an end-to-end fashion. This allows the tracker to be both computationally efficient and robust to appearance changes such as scale, rotation, and illumination variations. The repository provides pre-trained models, training code, and testing scripts for evaluating the tracker on standard benchmarks. ...

ECO (Efficient Convolution Operators for Tracking) is a high-performance object tracking algorithm developed by Martin Danelljan and collaborators. It is based on discriminative correlation filters and designed to handle appearance changes, occlusions, and scale variations in visual object tracking tasks. The code provides a MATLAB implementation of the ECO and ECO-HC (high-speed) variants and was one of the top performers on multiple visual tracking benchmarks.

...Because it fuses tracking and detection, TLD can recover from occlusions, drift, or failures by using its detection mechanism to reacquire the object. In terms of usage, one typically initializes the tracker by providing a bounding box on the first frame, then calls a function like run_TLD to process a video and obtain bounding boxes over time. The system updates its internal models as frames are processed, and can re-detect the target when tracking fails. The algorithm’s performance is known to improve over time due to its online adaptation behavior. ...