H
Hongbing Li
Researcher at Panasonic
Publications - 5
Citations - 159
Hongbing Li is an academic researcher from Panasonic. The author has contributed to research in topics: Data model & Security information and event management. The author has an hindex of 4, co-authored 5 publications receiving 159 citations.
Papers
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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
System architecture and process for automating intelligent surveillance center operations
TL;DR: In this paper, an intelligent, automated surveillance system collects the interactions between the security personal and the surveillance system during the handling of an alarm, each alarm is modeled as a transaction and each operation/action that a security personal executes modeled as an event within the transaction.
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.
Patent
Surveillance systems 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 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.