Sign language recognition allows computers to recognize the sign of a specific sign language, and afterwards translate it to a written language.
In 2015, with Franco Ronchetti we recorded LSA16 and LSA64, the first sign language datasets for the Argentinian Sign Language (Lengua de Señas Argentina, LSA) focused on training Computer Vision models. Afterwards, we’ve also contributed new recognition methods, analysis and tools.
Sign Language Datasets Survey
A survey of the available sign language datasets, with information such as number of samples/classes, goal (continuous/isolated,dynamic/static), etc.
Handshape datasets library
A single library to downloading and load handshape datasets. 10+ datasets supported
LSA16: Argentinian Sign Language Handshape Dataset
This database contains images of 16 handshapes of the Argentinian Sign Language (LSA), each performed 5 times by 10 different subjects, for a total of 800 images. The subjects wore color hand gloves and dark clothes.
LSA64: Argentinian Sign Language Dynamic Signs Dataset
A sign database for the Argentinian Sign Language, created with the goal of producing a dictionary for LSA and training an automatic sign recognizer, includes 3200 videos where 10 non-expert subjects executed 5 repetitions of 64 different types of signs.
Letters and Numbers Hand Gesture Dataset
Recorded with Kinect, 3d hand trajectory data