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Transform Space For Enhanced Multiple Object Tracking In Video Streams.pdf

isprs-annals-V-4-2022-137-2022.pdf
Preview of Transform Space for Enhanced Multiple Object Tracking in Video Streams
🔗 Source: isprs-annals.copernicus.org
📊 Size: 1.32 MB
📄 Pages: 7 pages
⬇️ Downloads: 66

Summary

Key contributions include:

1. Transform Space: Predicts trajectories on an estimated ground plane, converting detection results from image space to a more accurate transform space. This improves association accuracy by aligning with actual human motion.

2. Kalman Filter: Uses a Kalman filter in the transform space to predict object motions, enhancing tracking robustness.

3. Physical IOU: Employs physical ellipse intersection-over-union (IOU) for data association measurements instead of pixel-level bounding box IOU, reducing fragmentation caused by occlusion.

4. Cosine Metric Learning: Implements a model trained with an adaptive weighted triplet loss for robust appearance feature extraction, improving discrimination between similar objects.

Related Work:

- Spatial Information: Methods like SORT and RNN-based trackers use Kalman filters or recurrent neural networks to predict and associate object states based on spatial information.
- Appearance Features: Previous works integrate appearance features using Siamese networks, triplet losses, and LSTM networks to improve tracking performance, especially through occlusions.

Method Evaluation:

Extensive experiments demonstrate the proposed method's superior performance in reducing identity switches (IDSW) and fragmentations (Frag) compared to state-of-the-art techniques, validating its effectiveness in real-world applications like security management and autonomous driving.

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Description

A novel multiple object tracking (MOT) approach predicts physical locations and uses deep features to associate detections across frames, transforming object positions from image to estimated ground space for refined tracking.

Technical Information

  • File Format: PDF
  • File Size: 1.32 MB
  • Pages: 7
  • Language: EN
  • Total Downloads: 66
  • Last Updated: 2 hours ago

Document Overview

This PDF document about Transform Space for Enhanced Multiple Object Tracking in Video Streams provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Transform Space for Enhanced Multiple Object Tracking in Video Streams.

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If you're interested in Transform Space for Enhanced Multiple Object Tracking in Video Streams, you might also want to explore:

Transform guideTransform tutorialSpace guideSpace tutorialEnhanced guideEnhanced tutorialMultiple guideMultiple tutorialObject guideObject tutorialTracking guideTracking tutorialVideo guideVideo tutorialStreams guideStreams tutorial

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