Recognising online spatial activities using a bioinformatics inspired sequence alignment approach

Pattern Recognition

Volumn 41, Issue 11, 2008, Pages 3481-3492

  Riedel, Daniel E ^a   Venkatesh, Svetha ^a   Liu, Wanquan ^a  

^a CURTIN UNIVERSITY   (Australia)

Author keywords

Activity recognition; Bioinformatics; Dynamic time warping; Sequence alignment

Indexed keywords

ALIGNMENT; BIOCOMMUNICATIONS; BIOINFORMATICS; BOOLEAN FUNCTIONS; DATA MINING; DYNAMIC MODELS; DYNAMIC PROGRAMMING; INFORMATION SCIENCE; LEARNING SYSTEMS; MARKOV PROCESSES; MATHEMATICAL PROGRAMMING; NAVIGATION; SYSTEMS ENGINEERING; TWO DIMENSIONAL;

(2+1)-DIMENSIONAL; ACTIVITY DETECTION; APPLIED (CO); CLASSIFICATION PERFORMANCE; CONTINUOUS DATA; DATASTREAM (CO); DYNAMIC TIME WARPING (DTW); HIDDEN MARKOV MODEL (HMM); HIGHER PRECISION; LOCAL ALIGNMENT; ON-LINE RECOGNITIONS; ON-LINE TRACKING; ONLINE VIDEO; PROPERTY (S); SEQUENCE ALIGNMENTS; SEQUENCE SIMILARITY; SLIDING-WINDOW (SW); SMITH WATERMAN; SPATIAL DATA; SPATIAL SEQUENCES; VIDEO TRACKING;

HIDDEN MARKOV MODELS;

EID: 48149109438     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2008.04.019     Document Type: Article

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