scispace - formally typeset
Book ChapterDOI

A Fuzzy Rule-Based System with Ontology for Summarization of Multi-camera Event Sequences

Han-Saem Park, +1 more
- pp 850-860
TLDR
This paper focuses on getting diverse views for a single event using multi-camera system and deals with the problem of summarizing event sequences collected in the office environment based on this perspective, and confirms that the proposed method yields acceptable results.
Abstract
Recently, research for the summarization of video data has been studied a lot due to the proliferation of user created contents. Besides, the use of multiple cameras for the collection of the video data has been increasing, but most of them have used the multi-camera system either to cover the wide area or to track moving objects. This paper focuses on getting diverse views for a single event using multi-camera system and deals with the problem of summarizing event sequences collected in the office environment based on this perspective. Summarization includes camera view selection and event sequence summarization. View selection makes a single event sequence from multiple event sequences as selecting optimal views in each time, for which domain ontology based on the elements in an office environment and rules from questionnaire surveys have been used. Summarization generates a summarized sequence from a whole sequence, and the fuzzy rule-based system is used to approximate human decision making. The degrees of interests input by users are used in both parts. Finally, we have confirmed that the proposed method yields acceptable results using experiments of summarization.

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

A comprehensive survey of multi-view video summarization

TL;DR: An overview of the existing strategies proposed for MVS is presented, including their advantages and drawbacks, and the genericsteps in MVS, such as the pre-processing of video data, feature extraction, and post-processing followed by summary generation are described.
Journal ArticleDOI

MVS: A multi-view video synopsis framework

TL;DR: Experimental evaluations on standard datasets demonstrate the efficacy of the proposed framework over its counterparts concerning the reduction in synopsis length and retention of important actions.
Proceedings ArticleDOI

Automatic camera selection for activity monitoring in a multi-camera system for tennis

TL;DR: A system for automatic camera selection from a network of synchronised cameras within a tennis sporting arena that combines synchronised video streams from multiple cameras into a single summary video suitable for critical review by both tennis players and coaches is described and evaluated.
Proceedings ArticleDOI

A multi-view video synopsis framework

TL;DR: A simple framework for multi-view video synopsis is introduced by combining both the benefits of video summarization and video synopsis by compared with existing techniques, which shows a significant reduction in synopsis length with the proper inclusion of important objects.
Book ChapterDOI

Detecting Hidden Objects Using Efficient Spatio-Temporal Knowledge Representation

TL;DR: A fully intelligent system incorporating semantic, symbolic, and grounded information in a multi-view tracking system that uses temporal representations for automated reasoning and induction of knowledge about the multiple views of the studied scene in order to automatically detect salient or hidden objects of interest.
References
More filters
Journal ArticleDOI

Fuzzy data envelopment analysis (DEA): a possibility approach☆

TL;DR: The approach transforms fuzzy DEA models into possibility DEA models by using possibility measures of fuzzy events (fuzzy constraints) and it is shown that for the special case, in which fuzzy membership functions of fuzzy data are of trapezoidal types, possibility DEA model become linear programming models.
Journal ArticleDOI

Layered representations for learning and inferring office activity from multiple sensory channels

TL;DR: The use of layered probabilistic representations for modeling human activities is presented, and how the representation is used to do sensing, learning, and inference at multiple levels of temporal granularity and abstraction and from heterogeneous data sources is described.
Journal ArticleDOI

Predicting human interruptibility with sensors

TL;DR: This article presents a series of studies that quantitatively demonstrate that simple sensors can support the construction of models that estimate human interruptibility as well as people do, and therefore their use in everyday office environments is both practical and affordable.
Proceedings ArticleDOI

A proposal for an owl rules language

TL;DR: The expressive power of ORL is discussed, showing that the ontology consistency problem is undecidable, and how reasoning support for ORL might be provided are discussed.
Journal ArticleDOI

Multi camera image tracking

TL;DR: This paper presents a method for multi-camera image tracking in the context of image surveillance that exploits multiple camera views to resolve object occlusion and uses the Linear Kalman Filter, which is less cumbersome to implement than the Extended Kalman filter.
Related Papers (5)