Improving Object Tracking Accuracy in Video Sequences Subject to Noise and Occlusion Impediments by Combining Feature Tracking with Kalman Filtering.
Mark HeimbachKamak EbadiSally L. WoodPublished in: ACSSC (2018)
Keyphrases
- kalman filtering
- object tracking
- kalman filter
- video sequences
- partial occlusion
- particle filtering
- particle filter
- tracking framework
- image sequences
- mean shift
- moving objects
- visual tracking
- structure from motion
- appearance model
- video surveillance
- motion estimation
- computer vision
- multi camera
- video camera
- optical flow
- motion detection
- motion segmentation
- multiple cameras
- missing data
- sparse representation
- body parts
- viewpoint
- markov random field
- motion vectors
- surveillance system
- dynamic scenes
- human motion
- motion model
- moving camera
- ground plane
- feature extraction