Tracking and Planning for Surveillance Applications
Movies
(Unfortunatley different movie formats and codecs have been used. VideoLAN is recommended.)
Chapter 2. Road Target Tracking
Example 2.2: Simulated video (generated in a 3D sensor simulation tool) and detections. [Note! 70 MB]
Chapter 3. Planning for Surveillance and Reconnaissance
Example 3.7 [2 MB]
Example 3.8 [11 MB]
Black star: location of the sensor platform.
Red star: predicted position of the target.
Green star: true position of the target.
Blue circle: uncertainty ellipse of the target.
Paper A. Pedestrian Tracking with an Infrared Sensor using Road Network Information
Movie. [20 MB]
Paper B. Road Target Tracking with an Approximative Rao-Blackwellized Particle Filter
Section 7. Illustration of the tracking problem (BSPF). [0.7 MB]
Extra movie (not in the paper), similar case but different environment. [0.3 MB]
Paper D. Road Target Search and Tracking with Gimballed Vision Sensor on a UAV
Movies; Section 5.3. Example 3. Search on a grid; stationary UAV, no occlusion
Movies; Section 5.3. Example 4. Search on a grid; moving UAV, occlusion
Section 6.6. Extra movie 1 (not in the paper);
Same conditions as in the Sec 6.6 movie, but alpha is 1/10000, i.e., the planner focus more on searching for new targets, than re-discover known targets.Section 6.6. Extra movie 2 (not in the paper);
Same conditions as in the Sec 6.6 movie, but alpha is 1/10, i.e., the planner focus more on updating known targets, than searching for new.Section 6.7. Lab experiment with two targets (mp4, H.264)
Paper F. Information Based Planning for Aerial Exploration
PhD in Automatic Control
(Swedish: Doktor i reglerteknik)
- Address:
- Dept. of Electrical Engineering
- Linköping University
- SE-581 83 Linköping
- Sweden
Informationsansvarig: Per Skoglar
Senast uppdaterad: 2012-10-17