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Namsoo Joo
Researcher at Panasonic
Publications - 6
Citations - 216
Namsoo Joo is an academic researcher from Panasonic. The author has contributed to research in topics: Data model & Reference model. The author has an hindex of 5, co-authored 6 publications receiving 216 citations.
Papers
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Patent
Rule based intelligent alarm management system for digital surveillance system
TL;DR: An alarm management system includes an alarm receiver module receiving customized alarms from one or more of sensor devices and surveillance systems as mentioned in this paper, and an action handling module executes customized actions based on the evaluation.
Patent
System architecture and process for assessing multi-perspective multi-context abnormal behavior
TL;DR: In this article, a multi-perspective context sensitive behavior assessment system includes an adaptive behavior model builder establishing a real-time reference model that captures intention of motion behavior, which operates by modeling outputs of multiple user defined scoring functions with respect to multiple references of application specific target areas of interest.
Patent
Video surveillance system
TL;DR: In this paper, a video surveillance system is described, which includes a model database storing a plurality of models and a vector database storing vectors of recently observed trajectories, and a model building module that builds a new motion model corresponding to the motion data of the current trajectory data structure.
Patent
Method and system for scoring surveillance system footage
Hasan Timucin Ozdemir,Sameer Kibey,Lipin Liu,Kuo Chu Lee,Supraja Mosali,Namsoo Joo,Hongbing Li,Juan Yu +7 more
TL;DR: In this article, the authors proposed a learned decision-making method to produce progressive behavior and threat detection in a surveillance system, which is based on a learned data model and a learned scoring method.
Patent
Surveillance system and methods
Hasan Timucin Ozdemir,Sameer Kibey,Lipin Liu,Kuo Chu Lee,Supraja Mosali,Namsoo Joo,Hongbing Li,Juan Yu +7 more
TL;DR: In this paper, the authors proposed a learned decision-making method to produce progressive behavior and threat detection in a surveillance system, which is based on a learned data model and a learned scoring method.