Tasks processing Strong participation . Large results comparison on common tasks and video sequences . strong participation for classification & event recognition evaluation ETISEO Video Understanding Evaluation

Sequences processing Priority sequences have been processed . Partners produced strong efforts ETISEO Video Understanding Evaluation

Partners Metric results ETISEO Video Understanding Evaluation

Priority sequences - Results  for each task the mean, standard deviation, minimum and maximum of participant results for each priority sequences.  The task scores are computing using the mean of related task metrics notes (precision, sensitivity...). ETISEO Video Understanding Evaluation

Results – Priority sequences Mean and standard deviation of participant results on the priority sequences for detection and localisation tasks Mean 0.56, stand. Dev 0.23 ETISEO Video Understanding Evaluation

Results – Priority sequences Mean and standard deviation of participant results on the priority sequences for tracking Easier tracking Complex tracking ETISEO Video Understanding Evaluation

Results – Priority sequences Mean and standard deviation of participant results on the priority sequences for classification task ETISEO Video Understanding Evaluation

Results – Priority sequences Mean and standard deviation of participant results on the priority sequences for event recognition task Complex events Easier events ETISEO Video Understanding Evaluation

Results – Priority sequences Mean of participant results on the priority sequences for all tasks ETISEO Video Understanding Evaluation

Results Analysis Good scores for detection, localisation and tracking tasks - Detection precision: 0.63 - Localisation precision: 0.54 - high scores for merging/splitting and persistence/confusion metrics Low scores for classification and event recognition - less participant - dispersed results (differences between participants and sequences) - low sensitivity: not all object categories and events are recognised ETISEO Video Understanding Evaluation

Results Analysis For all metrics: - Mean Precision > Mean sensitivity: Missed Detection > False Detection => due to static objects annotation => not all object categories and events are recognised - More variations for precision results Precision = GD / (GD + FD) Sensitivity = GD / (GD + MD) Example for M1.2.1 Number of detected physical objects using their bounding boxes ETISEO Video Understanding Evaluation