Motion annotation in complex video datasets
Motion segmentation refers to the process of separating regions and trajectories from a video sequence into coherent subsets of space and time. In this thesis, we created a new multifaceted motion segmentation dataset enclosing real-life long and short sequences, with different numbers of motions an...
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| Tipo de recurso: | tesis doctoral |
| Estado: | Versión publicada |
| Fecha de publicación: | 2018 |
| País: | España |
| Institución: | CBUC, CESCA |
| Repositorio: | TDR. Tesis Doctorales en Red |
| OAI Identifier: | oai:www.tdx.cat:10803/667583 |
| Acceso en línea: | http://hdl.handle.net/10803/667583 |
| Access Level: | acceso abierto |
| Palabra clave: | Computer vision Visió per ordinador Visión por ordenador Motion segmentation Segmentació del moviment Segmentación del movimiento Image analysis Anàlisi d'imatges Análisis de imágenes Machine learning Aprenentatge automàtic Aprendizaje automático Automated tools Eines automàtiques Herarmientas automáticas Motion datasets 68 |
| Sumario: | Motion segmentation refers to the process of separating regions and trajectories from a video sequence into coherent subsets of space and time. In this thesis, we created a new multifaceted motion segmentation dataset enclosing real-life long and short sequences, with different numbers of motions and frames per sequence, and real distortions with missing data. Trajectory- and region-based ground-truth is provided on all the frames of all the sequences. We also proposed a new semi-automatic tool for delineating the trajectories in complex videos, even in videos captured from moving cameras. With a minimal manual annotation of an object mask, the algorithm is able to propagate the label mask in all the frames. Object label correction based on static and moving occluder is performed by applying occluder mask tracking for a given depth ordering. The results show that our cascaded-naive approach provides successful results in a variety of video sequences. |
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