Guy Ravitz - Academia.edu (original) (raw)

Papers by Guy Ravitz

IEEE Sixth International Symposium on Multimedia Software Engineering, 2004

Seventh IEEE International Symposium on Multimedia (ISM'05), 2005

In this paper, a multimodal unit detection framework to detect and extract units, a novel concept... more In this paper, a multimodal unit detection framework to detect and extract units, a novel concept towards event de- tection and extraction in sports TV broadcasts, is proposed. The proposed unit is defined to be a segment of a sports TV broadcast that describes a potentially interesting event, which possesses the potential of attracting the attention of the observer andsatisfy

2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008), 2008

2009 IEEE International Conference on Multimedia and Expo, 2009

2008 Tenth IEEE International Symposium on Multimedia, 2008

International Symposium on Multimedia, 2005

In this paper, a multimodal unit detection framework to detect and extract units, a novel concept... more In this paper, a multimodal unit detection framework to detect and extract units, a novel concept towards event de- tection and extraction in sports TV broadcasts, is proposed. The proposed unit is defined to be a segment of a sports TV broadcast that describes a potentially interesting event, which possesses the potential of attracting the attention of the observer andsatisfy

International Symposium on Multimedia Software Engineering, 2004

TREC Video Retrieval Evaluation, 2008

International Conference on Multimedia Computing and Systems/International Conference on Multimedia and Expo, 2009

Sensor Networks, Ubiquitous, and Trustworthy Computing, 2008

International Symposium on Multimedia, 2008

Semantic concept detection has emerged as an intriguing topic in multimedia research recently. Th... more Semantic concept detection has emerged as an intriguing topic in multimedia research recently. The ability to interpret high-level semantics from low-level features has been the long desired goal of many researchers. In this paper, we propose a novel framework that utilizes the ability of multiple correspondence analysis (MCA) to explore the correlation between different items (feature-value pairs) and classes (concepts) to bridge the gap between the extracted low-level features and high-level semantic concepts. Using the concepts and benchmark data identified and provided by the TRECVID project, we have shown that our proposed framework demonstrates promising results and performs better than the decision tree (DT),support vector machine (SVM), and naive Bayesian (NB) classifiers that are commonly applied to the TRECVID datasets.

IEEE Sixth International Symposium on Multimedia Software Engineering, 2004

Seventh IEEE International Symposium on Multimedia (ISM'05), 2005

In this paper, a multimodal unit detection framework to detect and extract units, a novel concept... more In this paper, a multimodal unit detection framework to detect and extract units, a novel concept towards event de- tection and extraction in sports TV broadcasts, is proposed. The proposed unit is defined to be a segment of a sports TV broadcast that describes a potentially interesting event, which possesses the potential of attracting the attention of the observer andsatisfy

International Conference on Multimedia Computing and Systems/International Conference on Multimedia and Expo, 2007

Digital audio and video have recently taken a center stage in the communication world, which high... more Digital audio and video have recently taken a center stage in the communication world, which highlights the importance of digital media information management and indexing. It is of great interest for the multimedia research community to find methods and solutions that could help bridge the semantic gap that exists between the low-level features extracted from the audio or video data and the actual semantics of the data. In this paper, we propose a novel framework that works towards reducing this semantic gap. The proposed framework uses the a priori algorithm and association rule mining to find frequent itemsets in the feature data set and generate classification rules to classify video shots to different concepts (semantics). We also introduce a novel pre-filtering architecture which reduces the high positive to negative instances ratio in the classifier training step. This helps reduce the amount of misclassification errors. Our proposed framework shows promising results in classifying multiple concepts.

2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008), 2008

International Journal of Software Engineering and Knowledge Engineering - IJSEKE, 2010

ABSTRACT Natural disasters, such as hurricanes, have had an enormous social and economical impact... more ABSTRACT Natural disasters, such as hurricanes, have had an enormous social and economical impact on society in the United State and around the world for many years. With the goal of preventing, diverting, or weakening the destructive forces of tropical cyclones, the preparedness of the public plays a major role in the magnitude of inflicted damage due to these storms. Acknowledging the captivating power of social networking and Web 2.0 over society, we present a prototype system which integrates meteorological data along with user generated content with the aim of improving public response by increasing their situational awareness due to such natural threats. The proposed system aggregates storm track and wind analysis data from the existing H*Wind system along with videos taken from YouTube and presents it to the user in Google Earth. A content-based concept detection mechanism is used to evaluate the relevance of the extracted YouTube videos to the storm of interest. The proposed system demonstrates the potential public benefit resulting from the integration of the areas of multimedia content analysis, Web 2.0, and meteorology.

2009 IEEE International Conference on Multimedia and Expo, 2009

2008 Tenth IEEE International Symposium on Multimedia, 2008

Information Reuse and Integration, 2009

Natural disasters, such as hurricanes, could have an enormous impact on society. The level of the... more Natural disasters, such as hurricanes, could have an enormous impact on society. The level of the public's preparedness could make a significant difference in the severity of casualty and damage inflicted by such storms. We present a prototype system to reach out to the public and improve their awareness of the potential dangers involved with such weather events. This Web-based system aggregates H*Wind storm track and wind fields data along with relevant videos extracted from YouTube and displays it to the user using Google Earth. A content-based concept detection algorithm is used to extract the videos, which may describe the impact of the storm in relevant geographic locations. Using Hurricane Ike as a case study, the result demonstrates how some of the information collected and displayed by the system could have increased the awareness of the public and potentially helped prepare them better to the devastating storm.

International Symposium on Multimedia, 2005

In this paper, a multimodal unit detection framework to detect and extract units, a novel concept... more In this paper, a multimodal unit detection framework to detect and extract units, a novel concept towards event de- tection and extraction in sports TV broadcasts, is proposed. The proposed unit is defined to be a segment of a sports TV broadcast that describes a potentially interesting event, which possesses the potential of attracting the attention of the observer andsatisfy

IEEE Sixth International Symposium on Multimedia Software Engineering, 2004

Seventh IEEE International Symposium on Multimedia (ISM'05), 2005

In this paper, a multimodal unit detection framework to detect and extract units, a novel concept... more In this paper, a multimodal unit detection framework to detect and extract units, a novel concept towards event de- tection and extraction in sports TV broadcasts, is proposed. The proposed unit is defined to be a segment of a sports TV broadcast that describes a potentially interesting event, which possesses the potential of attracting the attention of the observer andsatisfy

2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008), 2008

2009 IEEE International Conference on Multimedia and Expo, 2009

2008 Tenth IEEE International Symposium on Multimedia, 2008

International Symposium on Multimedia, 2005

In this paper, a multimodal unit detection framework to detect and extract units, a novel concept... more In this paper, a multimodal unit detection framework to detect and extract units, a novel concept towards event de- tection and extraction in sports TV broadcasts, is proposed. The proposed unit is defined to be a segment of a sports TV broadcast that describes a potentially interesting event, which possesses the potential of attracting the attention of the observer andsatisfy

International Symposium on Multimedia Software Engineering, 2004

TREC Video Retrieval Evaluation, 2008

International Conference on Multimedia Computing and Systems/International Conference on Multimedia and Expo, 2009

Sensor Networks, Ubiquitous, and Trustworthy Computing, 2008

International Symposium on Multimedia, 2008

Semantic concept detection has emerged as an intriguing topic in multimedia research recently. Th... more Semantic concept detection has emerged as an intriguing topic in multimedia research recently. The ability to interpret high-level semantics from low-level features has been the long desired goal of many researchers. In this paper, we propose a novel framework that utilizes the ability of multiple correspondence analysis (MCA) to explore the correlation between different items (feature-value pairs) and classes (concepts) to bridge the gap between the extracted low-level features and high-level semantic concepts. Using the concepts and benchmark data identified and provided by the TRECVID project, we have shown that our proposed framework demonstrates promising results and performs better than the decision tree (DT),support vector machine (SVM), and naive Bayesian (NB) classifiers that are commonly applied to the TRECVID datasets.

IEEE Sixth International Symposium on Multimedia Software Engineering, 2004

Seventh IEEE International Symposium on Multimedia (ISM'05), 2005

In this paper, a multimodal unit detection framework to detect and extract units, a novel concept... more In this paper, a multimodal unit detection framework to detect and extract units, a novel concept towards event de- tection and extraction in sports TV broadcasts, is proposed. The proposed unit is defined to be a segment of a sports TV broadcast that describes a potentially interesting event, which possesses the potential of attracting the attention of the observer andsatisfy

International Conference on Multimedia Computing and Systems/International Conference on Multimedia and Expo, 2007

Digital audio and video have recently taken a center stage in the communication world, which high... more Digital audio and video have recently taken a center stage in the communication world, which highlights the importance of digital media information management and indexing. It is of great interest for the multimedia research community to find methods and solutions that could help bridge the semantic gap that exists between the low-level features extracted from the audio or video data and the actual semantics of the data. In this paper, we propose a novel framework that works towards reducing this semantic gap. The proposed framework uses the a priori algorithm and association rule mining to find frequent itemsets in the feature data set and generate classification rules to classify video shots to different concepts (semantics). We also introduce a novel pre-filtering architecture which reduces the high positive to negative instances ratio in the classifier training step. This helps reduce the amount of misclassification errors. Our proposed framework shows promising results in classifying multiple concepts.

2008 IEEE International Conference on Sensor Networks, Ubiquitous, and Trustworthy Computing (sutc 2008), 2008

International Journal of Software Engineering and Knowledge Engineering - IJSEKE, 2010

ABSTRACT Natural disasters, such as hurricanes, have had an enormous social and economical impact... more ABSTRACT Natural disasters, such as hurricanes, have had an enormous social and economical impact on society in the United State and around the world for many years. With the goal of preventing, diverting, or weakening the destructive forces of tropical cyclones, the preparedness of the public plays a major role in the magnitude of inflicted damage due to these storms. Acknowledging the captivating power of social networking and Web 2.0 over society, we present a prototype system which integrates meteorological data along with user generated content with the aim of improving public response by increasing their situational awareness due to such natural threats. The proposed system aggregates storm track and wind analysis data from the existing H*Wind system along with videos taken from YouTube and presents it to the user in Google Earth. A content-based concept detection mechanism is used to evaluate the relevance of the extracted YouTube videos to the storm of interest. The proposed system demonstrates the potential public benefit resulting from the integration of the areas of multimedia content analysis, Web 2.0, and meteorology.

2009 IEEE International Conference on Multimedia and Expo, 2009

2008 Tenth IEEE International Symposium on Multimedia, 2008

Information Reuse and Integration, 2009

Natural disasters, such as hurricanes, could have an enormous impact on society. The level of the... more Natural disasters, such as hurricanes, could have an enormous impact on society. The level of the public's preparedness could make a significant difference in the severity of casualty and damage inflicted by such storms. We present a prototype system to reach out to the public and improve their awareness of the potential dangers involved with such weather events. This Web-based system aggregates H*Wind storm track and wind fields data along with relevant videos extracted from YouTube and displays it to the user using Google Earth. A content-based concept detection algorithm is used to extract the videos, which may describe the impact of the storm in relevant geographic locations. Using Hurricane Ike as a case study, the result demonstrates how some of the information collected and displayed by the system could have increased the awareness of the public and potentially helped prepare them better to the devastating storm.

International Symposium on Multimedia, 2005

In this paper, a multimodal unit detection framework to detect and extract units, a novel concept... more In this paper, a multimodal unit detection framework to detect and extract units, a novel concept towards event de- tection and extraction in sports TV broadcasts, is proposed. The proposed unit is defined to be a segment of a sports TV broadcast that describes a potentially interesting event, which possesses the potential of attracting the attention of the observer andsatisfy