Annotation tool designed for hazardous user behavior in guided mountain transport
Autor: | Cyril Meurie, Remi Dufour, Amaury Flancquart |
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Přispěvatelé: | Laboratoire Électronique Ondes et Signaux pour les Transports (IFSTTAR/COSYS/LEOST), Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)-PRES Université Lille Nord de France, Cadic, Ifsttar |
Jazyk: | angličtina |
Rok vydání: | 2018 |
Předmět: |
Facial motion capture
Computer science Image processing 02 engineering and technology Task (project management) Domain (software engineering) Annotation Software Human–computer interaction ALGORITHME ANNOTATION SOFTWARE 0202 electrical engineering electronic engineering information engineering GUIDED MOUNTAIN TRANS-PORT SECURITE TRAITEMENT DES IMAGES [SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing SECURITY VIDEO DATASET TRAITEMENT DES DONNEES SIMPLE (military communications protocol) business.industry 020207 software engineering COMPORTEMENT VISAGE BASE DE DONNEES FACE TRACKING Task analysis 020201 artificial intelligence & image processing business [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing IMAGE PROCESSING TOOL VIDEO |
Zdroj: | IPAS 2018, 3rd IEEE International Conference on Image Processing, Applications and Systems IPAS 2018, 3rd IEEE International Conference on Image Processing, Applications and Systems, Dec 2018, Sophia-Antipolis, France. 7p HAL Rémi Dufour IPAS |
Popis: | IPAS 2018, 3rd IEEE International Conference on Image Processing, Applications and Systems, Sophia-Antipolis, FRANCE, 12-/12/2018 - 14/12/2018; This paper proposes a semi-automatic ground truth annotation software designed for the specific needs of the EVEREST project. The purpose of this project is to build an annotated and anonymized video database, and use it to evaluate algorithms in the task of detecting hazardous behavior in guided mountain transport. To do so, a ground truth annotation tool that disposes designed specifically for the EVEREST project was needed. Ski lifts safety based on intelligent video systems is a niche domain which has not yet been explored in depth, which means no annotation tool suited for this task was available. That is why, we decided to develop a user-friendly and flexible tool to allows the semi-automatic annotation of events and faces (for privacy purposes). We looked at existing tracking algorithms, chose an implementation of TLD, and designed a new tracking algorithm that could be used when TLD isn't effective. This led to a simple, lightweight tracking algorithm that is more practical to use than the original CAMshift algorithm, and a user-friendly and flexible annotation tool that is well adapted to the specific task of annotating hazardous behavior in guided mountain transport. |
Databáze: | OpenAIRE |
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