Online Kernel Slow Feature Analysis for Temporal Video Segmentation and Tracking

IEEE Transactions on Image Processing

Volumn 24, Issue 10, 2015, Pages 2955-2970

  Liwicki, Stephan ^a,b   Zafeiriou, Stefanos P ^a   Pantic, Maja ^a,c  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY OF OXFORD   (United Kingdom)

^c UNIVERSITY OF TWENTE   (Netherlands)

Author keywords

Change detection; Online kernel learning; Slow feature analysis; Temporal segmentation; Tracking

Indexed keywords

COMPUTER VISION; IMAGE SEGMENTATION; SIGNAL DETECTION; SOCIAL NETWORKING (ONLINE); SURFACE DISCHARGES;

CHANGE DETECTION; CHANGE DETECTION ALGORITHMS; DIMENSIONALITY REDUCTION TECHNIQUES; ONLINE KERNEL LEARNING; SLOW FEATURE ANALYSIS; SLOW FEATURE ANALYSIS(SFA); TEMPORAL SEGMENTATIONS; TEMPORAL VIDEO SEGMENTATION;

E-LEARNING;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; AUTOMATED PATTERN RECOGNITION; BIOMIMETICS; COMPUTER ASSISTED DIAGNOSIS; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; PHOTOGRAPHY; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING; VIDEORECORDING;

ALGORITHMS; BIOMIMETICS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; NEURAL NETWORKS (COMPUTER); PATTERN RECOGNITION, AUTOMATED; PHOTOGRAPHY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SIGNAL PROCESSING, COMPUTER-ASSISTED; SUBTRACTION TECHNIQUE; VIDEO RECORDING;

EID: 84933040965     PISSN: 10577149     EISSN: None     Source Type: Journal    
DOI: 10.1109/TIP.2015.2428052     Document Type: Article

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