Multiple-Kernel Based Vehicle Tracking Using 3D Deformable Model and Camera Self-Calibration
Explore this paper's citation graph
Summary
A model-based vehicle localization method, which builds a kernel at each patch of the 3D deformable vehicle model and associates them with constraints in 3D space and outperforms both state-of-the-art of tracking by segmentation and tracking by detection.
- Type
- preprint
- Published
- 2017-08-22
- Cited by
- 23
- References
- 23
- Access
- Open access
- OpenAlex
- https://openalex.org/W2748159532
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:90888
Keywords
Calibration, Kernel (algebra), Computer vision, Tracking (education), Artificial intelligence
References
- An equalised global graphical model-based approach for multi-camera object tracking
- Estimation of Distribution Algorithms: A New Tool for Evolutionary Computation
- SuBSENSE: A Universal Change Detection Method With Local Adaptive Sensitivity
- Three-Dimensional Deformable-Model-Based Localization and Recognition of Road Vehicles
- Tracking Human Under Occlusion Based on Adaptive Multiple Kernels With Projected Gradients
- Multiple-kernel based vehicle tracking using 3-D deformable model and license plate self-similarity
- The Pascal Visual Object Classes Challenge: A Retrospective
- Mean Shift: A Robust Approach Toward Feature Space Analysis
- Robust video object tracking based on multiple kernels with projected gradients
- Human tracking by adaptive Kalman filtering and multiple kernels tracking with projected gradients
- Vehicle tracking iterative by Kalman-based constrained multiple-kernel and 3-D model-based localization
- Using vanishing points for camera calibration
- Simple online and realtime tracking
- MOT16: A Benchmark for Multi-Object Tracking
- Online Multi-Target Tracking Using Recurrent Neural Networks
- Multiple-kernel adaptive segmentation and tracking (MAST) for robust object tracking
- YOLO9000: Better, Faster, Stronger
- Camera self-calibration from tracking of moving persons
- Online-Learning-Based Human Tracking Across Non-Overlapping Cameras
- Inter-camera tracking based on fully unsupervised online learning
Cited by
- Single-Camera and Inter-Camera Vehicle Tracking and 3D Speed Estimation Based on Fusion of Visual and Semantic Features
- Joint Multi-View People Tracking and Pose Estimation for 3D Scene Reconstruction
- Vehicle Tracking and Speed Estimation from Traffic Videos
- Constrained Multi Camera Calibration for Lane Merge Observation
- Multi-camera vehicle tracking and re-identification based on visual and spatial-temporal features
- Vehicle Speed Measurement Based on Binocular Stereovision System
- PAMTRI: Pose-Aware Multi-Task Learning for Vehicle Re-Identification Using Highly Randomized Synthetic Data
- Accuracy Evaluation of Camera-based Vehicle Localization
- Video traffic estimation algorithm
- The 4th AI City Challenge
- ACCURATE VEHICLE SPEED ESTIMATION FROM MONOCULAR CAMERA FOOTAGE
- Native Vehicles Classification on Bangladeshi Roads Using CNN with Transfer Learning
- Modeling the Estimation Errors of Visual-based Systems Developed for Vehicle Speed Measurement
- Keyword-based Vehicle Retrieval
- Robust Automatic Monocular Vehicle Speed Estimation for Traffic Surveillance
- I see you: A Vehicle-Pedestrian Interaction Dataset from Traffic Surveillance Cameras
- Enhanced Vehicle Re-Identification for Smart City Applications Using Zone Specific Surveillance
- Bangladeshi Local Vehicle Recognition with A Comprehensive Dataset using Transfer Learning Techniques
- Deep-Feature-Based Visual Odometry for Autonomous Emergency Parking
- PATReId: Pose Apprise Transformer Network for Vehicle Re-Identification
Related papers
- Multiple-particle tracking—an improvement for positron particle tracking
- Tracking in Secondary Schools: A Contextual Perspective.
- Three-dimensional spatiotemporal tracking of fluorine-18 radiolabeled yeast cells via positron emission particle tracking
- An improved algorithm for tracking multiple, freely moving particles in a Positron Emission Particle Tracking system
- Analysis for Tracking Accuracy of a Space-borne Electro-optical Tracking System
- Tracking and back‐tracking
- Improved multiple‐particle tracking for studying flows in multiphase systems
- Tracking Walls, Take-It-Or-Leave-It Choices, the GDPR, and the ePrivacy Regulation