Performance Evaluation of People Tracking Systems
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
Performance Evaluation of Object Detection Algorithms
ICPR '02 Proceedings of the 16 th International Conference on Pattern Recognition (ICPR'02) Volume 3 - Volume 3
Steps toward a cognitive vision system
AI Magazine
Evaluating Multi-Object Tracking
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03
Performance evaluation in visual surveillance using the F-measure
Proceedings of the 4th ACM international workshop on Video surveillance and sensor networks
A Framework for Model-Based Tracking Experiments in Image Sequences
International Journal of Computer Vision
PETS Metrics: On-Line Performance Evaluation Service
ICCCN '05 Proceedings of the 14th International Conference on Computer Communications and Networks
Conceptual representations between video signals and natural language descriptions
Image and Vision Computing
IEEE Transactions on Pattern Analysis and Machine Intelligence
ETISEO, performance evaluation for video surveillance systems
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Dynamic Performance Measures for Object Tracking Systems
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
Urban Vehicle Tracking Using a Combined 3D Model Detector and Classifier
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part I
Multi-object tracking evaluated on sparse events
Multimedia Tools and Applications
Performance evaluation of object detection algorithms for video surveillance
IEEE Transactions on Multimedia
Vision, logic, and language - toward analyzable encompassing systems
KI'10 Proceedings of the 33rd annual German conference on Advances in artificial intelligence
| Hi-index | 0.00 |
The study of 3D-model-based tracking in videos frequently has to be concerned with details of algorithms or their parameterisation. Time-consuming experiments have to be performed in this context which suggested to (at least partially) automate the evaluation of such experimental runs. A logic-based approach has been developed which generates Natural Language textual descriptions of evaluation runs and facilitates the formulation of specific hints. The implementation of this approach is outlined, results obtained with it on an extended complex real-world road traffic video are presented and discussed.