Authors:
Julius Schöning
;
Patrick Faion
and
Gunther Heidemann
Affiliation:
University of Osnabrück, Germany
Keyword(s):
Semantic Ground Truth Annotation, Video Annotation, Polygon Shaped, Semi-automatic.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Image and Video Analysis
;
Image Understanding
;
Knowledge Acquisition and Representation
;
Pattern Recognition
;
Software Engineering
;
Theory and Methods
;
Video Analysis
Abstract:
In the last decades, a large diversity of automatic, semi-automatic and manual approaches for video segmentation and knowledge extraction from video-data has been proposed. Due to the high complexity in both the spatial and temporal domain, it continues to be a challenging research area. In order to develop, train, and evaluate new algorithms, ground truth of video-data is crucial. Pixel-wise annotation of ground truth is usually time-consuming, does not contain semantic relations between objects and uses only simple geometric primitives. We provide a brief review of related tools for video annotation, and introduce our novel interactive and semi-automatic segmentation tool iSeg. Extending an earlier implementation, we improved iSeg with a semantic time line, multithreading and the use of ORB features. A performance evaluation of iSeg on four data sets is presented. Finally, we discuss possible opportunities and applications of semantic polygon-shaped video annotation, such as 3D rec
onstruction and video inpainting.
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