2009
DOI: 10.1007/978-3-642-02577-8_14
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An Open Source Framework for Real-Time, Incremental, Static and Dynamic Hand Gesture Learning and Recognition

Abstract: Real-time, static and dynamic hand gesture learning and recognition makes it possible to have computers recognize hand gestures naturally. This creates endless possibilities in the way humans can interact with computers, allowing a human hand to be a peripheral by itself. The software framework developed provides a lightweight, robust, and practical application programming interface that helps further research in the area of human-computer interaction. Approaches that have proven in analogous areas such as spe… Show more

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Cited by 9 publications
(3 citation statements)
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“…Gesture recognition can provide a more natural and intuitive method for human-computer interaction compared with keyboard and mouse [1]. Dynamic gesture recognition based on machine vision captures hand gestures with a camera, and determines the interaction semantics of the gesture by calculating the correlation coefficient between the trajectory of gestures and the given templates [2][3][4][5].…”
Section: Introductionmentioning
confidence: 99%
“…Gesture recognition can provide a more natural and intuitive method for human-computer interaction compared with keyboard and mouse [1]. Dynamic gesture recognition based on machine vision captures hand gestures with a camera, and determines the interaction semantics of the gesture by calculating the correlation coefficient between the trajectory of gestures and the given templates [2][3][4][5].…”
Section: Introductionmentioning
confidence: 99%
“…Additionally, it has partially/indirectly supported an additional Masters thesis 21 . The REU research has also led to the publication with former undergraduate participants of 5 conference papers [22][23][24][25][26] (with undergraduates Hoover, Beck, Garcia, Cardona, Alexander, Ahmed, Sparks and Miguez) and 1 journal paper 27 (with undergraduate Hoover). Also, it has indirectly and subsequently aided in the research presented in 9 additional conferences and 2 journals, which we do not list here.…”
Section: A Research Outcomesmentioning
confidence: 99%
“…Οι Alexander κ.α. [60], χρησιμοποιούν τη διαφορά δύο στιγμιότυπων για να εντοπίσουν πιθανές περιοχές, οι οποίες μπορεί να περιέχουν χέρι, θεωρώντας ότι όταν ο χρήστης όταν πρόκειται να κάνει μια χειρονομία το χέρι του θα βρίσκεται σε κίνηση. Η διαφορά υπολογίζεται μεταξύ του τρέχοντος στιγμιότυπου και ενός στιγμιότυπου κλειδί το οποίο δεν μένει το ίδιο αλλά ενημερώνεται ανάλογα με την ποσότητα της κίνησης που ανιχνεύεται.…”
Section: σχετικές εργασίεςunclassified