Object Tracking with Correlation Filters using Selective Single Background Patch
This is an incremental improvement for computer vision researchers working on object tracking.
The paper tackles object tracking by proposing a method to select a single background patch and modifying correlation filters with image restoration filters, achieving improved tracking performance validated on Object Tracking Benchmark sequences.
Correlation filter plays a major role in improved tracking performance compared to existing trackers. The tracker uses the adaptive correlation response to predict the location of the target. Many varieties of correlation trackers were proposed recently with high accuracy and frame rates. The paper proposes a method to select a single background patch to have a better tracking performance. The paper also contributes a variant of correlation filter by modifying the filter with image restoration filters. The approach is validated using Object Tracking Benchmark sequences.