Download NUS Hand Posture Data set I (Zipped file)
The NUS hand posture data set I consists 10 classes of postures, 24 sample images per class, which are captured by varying the position and size of the hand within the image frame. Both grey-scale and color images are available (160×120 pixels). The hand postures are selected in such a way that the inter class variation in the appearance of the postures is less, which makes the recognition task challenging.
This data set is used to test the recognition accuracy of the algorithm reported in the article, “Pramod Kumar P, Prahlad Vadakkepat, and Loh Ai Poh, Hand posture and face recognition using a Fuzzy-Rough Approach”, International Journal of Humanoid Robotics, vol.7, no.3, pp.331-356, September, 2010. The data set can be used for academic research purposes free of cost, by citing the article.
PS: The background of the images in this dataset is uniform. Another hand posture dataset containing images with complex background is available in the NUS Hand Posture Data set-II.
Download NUS Hand Posture Data set II (Zipped file)
This is a 10 class hand posture data set. The postures are shot in and around National University of Singapore (NUS), against complex natural backgrounds, with various hand shapes and sizes. The postures are performed by 40 subjects, with different ethnicity, against different complex backgrounds. The subjects include both males and females in the age range of 22 to 56 years. The subjects are asked to show the 10 hand postures, 5 times each. They are asked to loosen the hand muscle after each shot, in order to incorporate the natural variations in the postures.
The dataset also consist of a set of background images which does not contain any of the hand postures.
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