A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
Machine Learning
The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
Multimodal Video Indexing: A Review of the State-of-the-art
Multimedia Tools and Applications
Evaluating the application of semantic inferencing rules to image annotation
Proceedings of the 3rd international conference on Knowledge capture
An Ontology for Event Detection and its Application in Surveillance Video
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
| Hi-index | 0.00 |
Segmentation and representation of movements in videos play an important role in different applications such as search engines, video recommender systems, and video summarizers. In this paper, we present a system for semantic annotation of movements in video. This system is based on the temporal segmentation method that extracts the movement objects in still scenes, and on the high-level movement concepts to bridge the semantic gap between such concepts and the low-level video features. We propose a knowledge-based Model of movements in videos by using the OWL ontology and SWRL rules. Our Video Movement Ontology (VMO) considers different concepts related to the relevant movement features, which is based on the semantic of the Benesh Movement Notation (BMN). BMN can describe any form of dance or human movement. Rules in description logic are defined to describe how low-level features and mapping process between those features and ontology's concepts should be applied according to different perception of video content analysis. This system can improve the quality of annotation of movements in the videos and can discover the hidden information by reasoning video knowledge and movement's features.