A framework for robust object multi-detection with a vote aggregation and a cascade filtering
This paper presents a framework designed for the multi-object detection purposes and adjusted for the application of product search on the market shelves. The framework uses a single feedback loop and a pattern resizing mechanism to demonstrate the top effectiveness of the state-of-the-art local features. A high detection rate with a low false detection chance can be achieved with use of only one pattern per object and no manual parameters adjustments. The method incorporates well known local features and a basic matching process to create a reliable voting space. Further steps comprise of metric transformations, graphical vote space representation, two-phase vote aggregation process and a cascade of verifying filters.
Code (0)
등록된 구현이 없습니다.
Tasks
Objectobject-detectionObject DetectionSimilar Papers 제목 키워드 기반
Robust Method of Vote Aggregation and Proposition Verification for Invariant Local Features
This paper presents a method for analysis of the vote space created from the local features extraction process in a multi-detection system. The method is opposed to the classic clustering approach and gives a high level …
Clusteringobject-detectionObject Detection3D-MPA: Multi Proposal Aggregation for 3D Semantic Instance Segmentation
We present 3D-MPA, a method for instance segmentation on 3D point clouds. Given an input point cloud, we propose an object-centric approach where each point votes for its object center. We sample object proposals from th…
3D Instance Segmentation3D Object Detection3D Semantic Instance SegmentationObject+13D-MPA: Multi-Proposal Aggregation for 3D Semantic Instance Segmentation
We present 3D-MPA, a method for instance segmentation on 3D point clouds. Given an input point cloud, we propose an object-centric approach where each point votes for its object center. We sample object proposals from th…
3D Object Detection3D Semantic Instance SegmentationInstance SegmentationObject+3VENet: Voting Enhancement Network for 3D Object Detection
Hough voting, as has been demonstrated in VoteNet, is effective for 3D object detection, where voting is a key step. In this paper, we propose a novel VoteNet-based 3D detector with vote enhancement to improve the de…
3D Object DetectionObjectobject-detectionObject DetectionSAVTrack: Selective Vote Aggregation for Reliability-Aware Point Cloud Tracking
3D single object tracking (SOT) in LiDAR point clouds is essential for autonomous systems, but remains challenging under sparse and incomplete observations. In such cases, different target points provide highly uneven co…
Object TrackingPoint Clouds