Tracking a person with 3D motion by integrating optical flow and depth

Systems and Computers in Japan

Volumn 32, Issue 7, 2001, Pages 29-38

  Okada, Ryuzo ^a   Shirai, Yoshiaki ^b   Miura, Jun ^b   Kuno, Yoshinori ^b  

^a TOSHIBA CORPORATION   (Japan)

^b OSAKA UNIVERSITY   (Japan)

Author keywords

Optical flows disparity; Segmentation; Sensor fusion; Three dimensional tracking

Indexed keywords

FEATURE EXTRACTION; IMAGE QUALITY; IMAGE SEGMENTATION; KALMAN FILTERING; MOTION ESTIMATION; OPTICAL FLOWS; PROBABILITY; SENSOR DATA FUSION; STATE ESTIMATION;

DEPTH; DISPARITY; THREE DIMENSIONAL TRACKING;

IMAGE PROCESSING;

EID: 0035973101     PISSN: 08821666     EISSN: None     Source Type: Journal    
DOI: 10.1002/scj.1039     Document Type: Article

References (20)

1. Automatic analysis of moving image
2. Robot vision system with a correlation chip for real-time tracking, optical flow and depth map generation
3. Real-time smooth pursuit tracking for a moving binocular robot
4. Realtime multiple object tracking based on optical flows
5. Detecting multiple rigid image motions from an optical flow field obtained with multi-scale, multi-orientation filters
6. Region segmentation and tracking of moving pictures based on clustering of position, color and motion
7. Robust multiple car tracking with occlusion reasoning
8. Towards an active visual observer
9. Object tracking based on optical flow and depth information
10. Person tracking by integrating optical flow and uniform brightness regions
11. 2-D motion estimation by region segmentation based on color, position and intensity gradients
12. Real-time tracking of multiple moving objects in moving camera image sequence using robust statistics
13. A method of motion recognition from stereo images for human image synthesis
14. Tracking non-rigid objects in complex scenes
15. Cardboard people: A parameterized model of articulated image motion
16. Tracking moving object in 3-D space based on optical flow and edges
17. Image tracking of persons with 3-D motions
18. Inherent ambiguities in recovering 3-D motion and structure from a noisy flow field
19. Dimensional analysis
20. Kalman filters