REAL-TIME DETECTION-BASED MODELING OF FINGER SEGMENTS

摘要

The bottleneck of many data-intensive and business-criticalrnapplications used to be the available computing power.rnWith the advent of distributed computing and data mining,rna new frontier is now the efficient manual explorationrnof large data to elucidate business value. This paper describesrna novel vision-based hand modeling system as onernstep towards new ways of naturally interacting with largernheterogeneous data. The many degrees of freedom of thernhand make it uniquely suited to this purpose, but also poserna computational challenge in automatic reconstruction. Wernaspire to obtain real-time performance in a purely frameby-rnframe detection-based architecture and meet this challengernby combining bottom-up hypothesis generation withrntop-down pruning. As real data is critical for training, wernfurthermore describe a novel method for gathering largerncorpora of automatically annotated hand data. Our experimentsrnwere conducted on 13 users under large pose variabilityrnof both male and female hands.