James H. Errico

Content-based filtering and personalization using structured metadata

Structured descriptions of multimedia content and automatically generated user profiles are used to filter content.

Bridging the semantic gap in sports

One of the major challenges facing current media management systems and the related applications is the so-called “semantic gap” between the rich meaning that a user desires and the shallowness of the content descriptions that are automatically extracted from the media. In this paper, we address the problem of bridging this gap in the sports domain. We propose a general framework for indexing and summarizing sports broadcast programs. The framework is based on a high-level model of sports broadcast video using the concept of an event, defined according to domain-specific knowledge for different types of sports. Within this general framework, we develop automatic event detection algorithms that are based on automatic analysis of the visual and aural signals in the media. We have successfully applied the event detection algorithms to different types of sports including American football, baseball, Japanese sumo wrestling, and soccer. Event modeling and detection contribute to the reduction of the semantic gap by providing rudimentary semantic information obtained through media analysis. We further propose a novel approach, which makes use of independently generated rich textual metadata, to fill the gap completely through synchronization of the information-laden textual data with the basic event segments. An MPEG-7 compliant prototype browsing system has been implemented to demonstrate semantic retrieval and summarization of sports video.

Presence based collaborative recommender for networked audiovisual displays

In this paper, we describe a presence based collaborative recommender (PBCR) system for networked audiovisual (AV) displays such as Internet connected TV sets with access to broadcast TV programs over traditional channels, video on demand, and Internet Protocol (IP) AV programs. The proposed PBCR system is based on presence technology and provides viewers with collaborative recommendations on AV programs based on presence or ratings of users within viewers community.