A fast approach to novelty detection in video streams using recursive density estimation

2008 4th International IEEE Conference Intelligent Systems, IS 2008

Volumn 3, Issue , 2008, Pages 142-147

  Ramezani, Ramin ^a   Angelov, Plamen ^a   Zhou, Xiaowei ^a  

^a Digital Signal Processing Research Group   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CHARACTERISTIC; AUTONOMOUS TRACKING SYSTEM; BACKGROUND MODEL; BACKGROUND SUBTRACTION; CLUSTERING APPROACH; COMPUTATIONALLY EFFICIENT; COUNTER TERRORISM; DENSITY ESTIMATION; GAUSSIANS; HUMAN OPERATOR; HUMAN SAFETY; KERNEL DENSITY ESTIMATION; KEY ELEMENTS; LANDMARK RECOGNITION; MEMORY STORAGE; NEW APPROACHES; NOVELTY DETECTION; ONLINE LEARNING; ORDER OF MAGNITUDE; POTENTIAL APPLICATIONS; REAL-TIME APPLICATION; REAL-TIME PREDICTION; RECURSIVE EXPRESSIONS; ROBOTIC SYSTEMS; SELF-LOCALIZATION; STAND -ALONE; STATE-OF-THE-ART APPROACH; TAKAGI SUGENO FUZZY MODELS; TRACKING ALGORITHM; VIDEO STREAMS;

DETECTORS; ESTIMATION; FUZZY FILTERS; IMAGE SEGMENTATION; INTELLIGENT SYSTEMS; MATHEMATICAL OPERATORS; ROBOTICS; SECURITY SYSTEMS; TERRORISM; TRACKING (POSITION); VIDEO STREAMING;

REAL TIME SYSTEMS;

EID: 77955753212     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IS.2008.4670523     Document Type: Conference Paper

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