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Automatic sign language recognition provides better services to the deaf as it avoids the existing communication gap between them and the rest of the society. Hand gestures, the primary mode of sign language communication, plays a key role in improving sign language recognition. This article presents a video dataset of the hand gestures of Indian sign language (ISL) words used in emergency situations. The videos of eight ISL words have been collected from 26 individuals (including 12 males and 14 females) in the age group of 22 to 26 years with two samples from each individual in an indoor environment with normal lighting conditions. Such a video dataset is highly needed for automatic recognition of emergency situations from the sign language for the benefit of the deaf. The dataset is useful for the researchers working on vision based sign language recognition (SLR) as well as hand gesture recognition (HGR). Moreover, support vector machine based classification and deep learning based classification of the emergency gestures has been carried out and the base classification performance shows that the database can be used as a benchmarking dataset for developing novel and improved techniques for recognizing the hand gestures of emergency words in Indian sign language.

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