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David Samuel Friedlander
Publications - 17
Citations - 507
David Samuel Friedlander is an academic researcher. The author has contributed to research in topics: Object (computer science) & Cluster analysis. The author has an hindex of 12, co-authored 17 publications receiving 507 citations.
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Patent
Behavioral recognition system
John Eric Eaton,Wesley Kenneth Cobb,Dennis G. Urech,Blythe Bobby Ernest,David Samuel Friedlander,Rajkiran Kumar Gottumukkal,Lon W. Risinger,Kishor Adinath Saitwal,Ming-Jung Seow,David M. Solum,Gang Xu,Tao Yang +11 more
TL;DR: In this article, a method and a system for analyzing and learning behavior based on an acquired stream of video frames is presented. But the method is not suitable for real-time applications.
Patent
Semantic representation module of a machine-learning engine in a video analysis system
John Eric Eaton,Wesley Kenneth Cobb,Dennis G. Urech,David Samuel Friedlander,Gang Xu,Ming-Jung Seow,Lon W. Risinger,David M. Solum,Tao Yang,Rajkiran Kumar Gottumukkal,Kishor Adinath Saitwal +10 more
TL;DR: In this article, a machine learning engine is described that is configured to recognize and learn behaviors, as well as to identify and distinguish between normal and abnormal behavior within a scene, by analyzing movements and/or activities (or absence of such) over time.
Patent
Long-term memory in a video analysis system
TL;DR: In this paper, a long-term memory used to store and retrieve information learned while a video analysis system observes a stream of video frames is disclosed, where the size of a feature dimension (used to determine the similarity between different observed events) may grow dynamically as necessary, depending on the actual events observed in a sequence of videos.
Patent
Identifying anomalous object types during classification
Wesley Kenneth Cobb,David Samuel Friedlander,Rajkiran Kumar Gottumukkal,Ming-Jung Seow,Gang Xu +4 more
TL;DR: In this article, a self-organizing map and adaptive resonance theory (SOM-ART) network is used to discover object type clusters and classify objects depicted in the image data based on pixel-level micro-features that are extracted from the image.
Patent
Video surveillance system configured to analyze complex behaviors using alternating layers of clustering and sequencing
TL;DR: In this article, techniques for a video surveillance system to learn to recognize complex behaviors by analyzing pixel data using alternating layers of clustering and sequencing are described, where each layer identifies what events and behaviors are common and which are unusual.