Self-adaptive Gaussian mixture models for real-time video segmentation and background subtraction

Proceedings of the 2010 10th International Conference on Intelligent Systems Design and Applications, ISDA'10

Volumn , Issue , 2010, Pages 983-989

  Greggio, Nicola ^a,b   Bernardino, Alexandre ^a   Laschi, Cecilia ^b   Dario, Paolo ^b   Santos Victor, José ^a  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^b SCUOLA SUPERIORE SANT ANNA   (Italy)

Author keywords

Background subtraction; Online EM; Real time video segmentation; Self adapting Gaussian mixtures

Indexed keywords

BACKGROUND SUBTRACTION; BEST MODEL; COMPLEX MODEL; COMPUTATIONAL REQUIREMENTS; FOREGROUND/BACKGROUND; GAUSSIAN MIXTURE MODEL; MULTIPLE MOVING OBJECTS; ONLINE EM; REAL TIME TRACKING; REAL-TIME VIDEO SEGMENTATION; SEGMENTATION PERFORMANCE; SELF-ADAPTING GAUSSIAN MIXTURES; SELF-ADAPTIVE; STATISTICAL FRAMEWORK; VIDEO FRAME; VIDEO SEGMENTATION; VIDEO SEQUENCES;

ARRAY PROCESSING; GAUSSIAN DISTRIBUTION; INTELLIGENT SYSTEMS; MIXTURES; SYSTEMS ANALYSIS;

IMAGE SEGMENTATION;

EID: 79851483756     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ISDA.2010.5687059     Document Type: Conference Paper

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