Correlation Tracking via Robust Region Proposals
Recently, correlation filter-based trackers have received extensive attention due to their simplicity and superior speed. However, such trackers perform poorly when the target undergoes occlusion, viewpoint change or other challenging attributes due to pre-defined sampling strategy. To tackle these issues, in this paper, we propose an adaptive region proposal scheme to facilitate visual tracking. To be more specific, a novel tracking monitoring indicator is advocated to forecast tracking failure. Afterwards, we incorporate detection and scale proposals respectively, to recover from model drift as well as handle aspect ratio variation. We test the proposed algorithm on several challenging sequences, which have demonstrated that the proposed tracker performs favourably against state-of-the-art trackers.
Code (0)
등록된 구현이 없습니다.
Tasks
Region ProposalVisual TrackingSimilar Papers 제목 키워드 기반
Correlation filter tracking with adaptive proposal selection for accurate scale estimation
Recently, some correlation filter based trackers with detection proposals have achieved state-of-the-art tracking results. However, a large number of redundant proposals given by the proposal generator may degrade the pe…
Object TrackingVisual Object TrackingTrack and Segment: An Iterative Unsupervised Approach for Video Object Proposals
We present an unsupervised approach that generates a diverse, ranked set of bounding box and segmentation video object proposals---spatio-temporal tubes that localize the foreground objects---in an unannotated video. In…
Segmentation3D-SiamRPN: An End-to-End Learning Method for Real-Time 3D Single Object Tracking Using Raw Point Cloud
3D single object tracking is a key issue for autonomous following robot, where the robot should robustly track and accurately localize the target for efficient following. In this paper, we propose a 3D tracking method ca…
3D Single Object TrackingObjectObject TrackingRegion ProposalTLPG-Tracker: Joint Learning of Target Localization and Proposal Generation for Visual Tracking.
Target localization and proposal generation are two essential subtasks in generic visual tracking, and it is a challenge to address both the two efficiently. In this paper, we propose an efficient two-stage architecture …
Visual TrackingMeta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation
Few-shot object detection has been extensively investigated by incorporating meta-learning into region-based detection frameworks. Despite its success, the said paradigm is still constrained by several factors, such as (…
Few-Shot Object DetectionMeta-LearningObjectobject-detection+1