Model-based object tracking in monocular image sequences of road traffic scenes
International Journal of Computer Vision
Robust multiple car tracking with occlusion reasoning
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Signal Processing - Video segmentation for content-based processing manipulation
Robust Tracking of Position and Velocity With Kalman Snakes
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Real-time Computer Vision System for Measuring Traffic Parameters
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Geodesic Active Regions for Supervised Texture Segmentation
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Automatic segmentation of moving objects for video object plane generation
IEEE Transactions on Circuits and Systems for Video Technology
Unsupervised video segmentation based on watersheds and temporal tracking
IEEE Transactions on Circuits and Systems for Video Technology
Semiautomatic segmentation and tracking of semantic video objects
IEEE Transactions on Circuits and Systems for Video Technology
MMDB '03 Proceedings of the 1st ACM international workshop on Multimedia databases
Automatic extraction of motion trajectories in compressed sports videos
Proceedings of the 12th annual ACM international conference on Multimedia
Multimedia Tools and Applications
A real-time object detecting and tracking system for outdoor night surveillance
Pattern Recognition
Interaction between high-level and low-level image analysis for semantic video object extraction
EURASIP Journal on Applied Signal Processing
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Automatic detection of salient objects and spatial relations in videos for a video database system
Image and Vision Computing
Detecting and tracking distant objects at night based on human visual system
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
Using adaptive background subtraction into a multi-level model for traffic surveillance
Integrated Computer-Aided Engineering
| Hi-index | 0.00 |
We present an automatic video object tracking algorithm capable of dealing with multiple simultaneous objects. The tracking is based on interactions between high-level and low-level image analysis results. The high-level result is a partition defining video objects, and the low-level result is a partition formed by homogeneous regions. For each region, a set of characteristic descriptors is produced. These region descriptors, and not regions themselves, are used to track the regions (and thus the objects) along time. Track management issues such as appearance and disappearance of objects, splitting and partial occlusions are resolved through interactions between regions and objects. Defining the tracking based on the parts of objects, identified by region segmentation, has led to a flexible technique that exploits the nature of the video object tracking problem. Experimental results show that the proposed method is able to track multiple rigid and deformable objects in indoor and outdoor scenes.