Implement Objects Detection and Tracking Using Points Cloud Reconstructed from Linear Stereo Vision

[mslavescu]

Objects Detection and Tracking Using Points Cloud Reconstructed from Linear Stereo Vision
https://www.intechopen.com/books/current-advancements-in-stereo-vision/objects-detection-and-tracking-using-points-cloud-reconstructed-from-linear-stereo-vision

7. Conclusion
   A method for detecting and tracking objects using linear stereo vision is presented. After
   reconstructing 3D points from the matching edge points extracted from stereo linear images,
   a clustering algorithm based on a spectral analysis is proposed to extract clusters of points
   where each cluster represents an object of the observed scene. The tracking process is
   achieved using Kalman filter algorithm and nearest neighbour data association. A fusion
   strategy is also proposed to resolve the problem of multiple clusters that represent a same
   object. The proposed method is tested with real data in the context of objects detection and
   tracking in front of a vehicle. �

See more articles in this area:

https://scholar.google.ca/scholar?q=Objects+Detection+and+Tracking+Using+Points+Cloud+Reconstructed+from+Linear+Stereo+Vision

[mslavescu]

Would be great to have a live demo in Google Colaboratoty

[angelocarbone]

I'm studying the official document listed below:

http://cdn.intechopen.com/pdfs/37773/InTech-Objects_detection_and_tracking_using_points_cloud_reconstructed_from_linear_stereo_vision.pdf

I'll try to do a summary