Download the software package released under the GNU Public License.
If you use this software (or a modified version of it) in any scientific work, please cite the corresponding paper:
Radu Tudor Ionescu, Marius Popescu, Christopher Conly, Vassilis Athitsos. Local Frame Match Distance: A Novel Approach for Exemplar Gesture Recognition. Proceedings of EUSIPCO, pp. 818–822, August 2017. [BibTeX] [Download PDF]
Gesture recognition using a training set of limited size for a large vocabulary of gestures is a challenging problem in computer vision. With few examples per gesture class, researchers often employ state-of-the-art exemplar-based methods such as Dynamic Time Warping (DTW).
As an alternative to DTW, we introduce the Local Frame Match Distance (LFMD), a novel approach for matching gestures inspired by a distance measure for strings, namely Local Rank Distance (LRD). While LRD efficiently approximates the non-alignment of character n-grams between two strings, we employ LFMD to efficiently measure the non- alignment of hand locations between two video sequences.
The empirical results indicate that our method can generally yield better performance than a state-of-the-art DTW approach on the challenging task of American Sign Language recognition, while reducing the computational time by 30%.
Download the software package containing Java and Matlab code for both Local Frame Match Distance (LFMD) and Dynamic Time Warping (DTW). The software is released under the GNU Public License. Please cite the paper if you use this software in your scientific work.