Amazon disputes those findings. And it notes that the paper in question failed to make clear the confidence threshold — i. In a statement provided to VentureBeat, Dr. Matt Wood, general manager of deep learning and AI at AWS, drew a distinction between facial analysis — which is concerned with spotting faces in videos or images and assigning generic attributes to them — and facial recognition, which matches an individual face to faces in videos and images. This is the same approach used to unlock some phones, or authenticate somebody entering a building, or by law enforcement to narrow the field when attempting to identify a person of interest. A majority of the false matches — 38 percent — were people of color.
MIT researchers: Amazon’s Rekognition shows gender and ethnic bias (updated)
Faces of the World -- National Geographic
All relevant data are within the paper. Classification or typology systems used to categorize different human body parts have existed for many years. Nevertheless, there are very few taxonomies of facial features. Ergonomics, forensic anthropology, crime prevention or new human-machine interaction systems and online activities, like e-commerce, e-learning, games, dating or social networks, are fields in which classifications of facial features are useful, for example, to create digital interlocutors that optimize the interactions between human and machines. However, classifying isolated facial features is difficult for human observers. Previous works reported low inter-observer and intra-observer agreement in the evaluation of facial features. This work presents a computer-based procedure to automatically classify facial features based on their global appearance.
Automatic classification of human facial features based on their appearance
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When benchmarking an algorithm it is recommendable to use a standard test data set for researchers to be able to directly compare the results. While there are many databases in use currently, the choice of an appropriate database to be used should be made based on the task given aging, expressions, lighting etc. Another way is to choose the data set specific to the property to be tested e. Li and Anil K. Jain, ed.