Visual Players Detection and Tracking in Soccer Matches
AVSS '08 Proceedings of the 2008 IEEE Fifth International Conference on Advanced Video and Signal Based Surveillance
ETISEO, performance evaluation for video surveillance systems
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
A novel histogram-based feature representation and its application in sport players classification
ISVC'10 Proceedings of the 6th international conference on Advances in visual computing - Volume Part III
Bayesian loop for synergistic change detection and tracking
ACCV'10 Proceedings of the 2010 international conference on Computer vision - Volume Part I
Proceedings of the International Working Conference on Advanced Visual Interfaces
A semi-automatic tool for detection and tracking ground truth generation in videos
Proceedings of the 1st International Workshop on Visual Interfaces for Ground Truth Collection in Computer Vision Applications
Monocular object detection using 3d geometric primitives
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part I
Synthetic Video Generation for Evaluation of Sprite Generation
International Journal of Multimedia Data Engineering & Management
ACCV'12 Proceedings of the 11th Asian conference on Computer Vision - Volume Part III
People reidentification in surveillance and forensics: A survey
ACM Computing Surveys (CSUR)
Accurate ball detection in soccer images using probabilistic analysis of salient regions
Machine Vision and Applications
Soccer video and player position dataset
Proceedings of the 5th ACM Multimedia Systems Conference
Take your eyes off the ball: Improving ball-tracking by focusing on team play
Computer Vision and Image Understanding
| Hi-index | 0.00 |
The problem of ground truth generation is fundamental for many approaches of computer vision and image processing. In order to test algorithms for object segmentation, object tracking, object interactions, it is necessary to have image sequences in which the ground truth is determined in an objective way. In the context of visual surveillance where many people moves in the scene occluding each other, it could be very complex and hard the work of generating for each image the position of all the moving objects and maintain this information for all the period in which they remain in the scene. In this paper we propose a semi-automatic system that generatesan initial ground truth estimation, and then provides a user-friendly interface to manually validate or correct the track results. The proposed system has been tested on some soccer video sequences that have been published on-line for being available to the scientific community, but it can be used also in other surveillance contexts.