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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=http://users.cecs.anu.edu.au/~adhall&rft.title=Acted Facial Expressions In The Wild&rft.identifier=canberra.edu.au/Collection/Dafeitwd001&rft.publisher=University of Canberra&rft.description=Quality data recorded in varied realistic environments is vital for effective human face related research. Currently available datasets for human facial expression analysis have been generated in highly controlled lab environments. We present a new dynamic 2D facial expressions database based on movies capturing diverse scenarios. A new XML schema based approach has been developed for the database collection and distribution tools. Realistic face data plays a vital role in the research advancement of facial expression analysis systems. We have named our database Acted Facial Expressions in the Wild similar to the spirit of the Labeled Faces in the Wild (LFW) database. It contains 957 videos in AVI format labelled with six basic expressions Angry, Happy, Disgust, Fear, Sad, Surprise and the Neutral expression. We also wanted to capture the information on how facial expressions evolved in subjects with age. Therefore we have chosen sets of movies featuring the same actors. For example, the Harry Potter series forms a good platform to analyse how facial expressions of subjects evolve with age. We used thirty-seven movies from a diverse range of movie genres so as to cover as much varied expressions and natural environments as possible. Much progress has been made in the fields of face recognition and human activity recognition in the past years due to the availability of realistic databases as well as robust representation and classification techniques. Inspired by them, we present a labelled temporal facial expression database from movies. Human facial expression databases till now have been captured in controlled ‘lab’ environments.&rft.creator=Australian National University&rft.creator=University of Canberra&rft.creator=Dr Roland Goecke&rft.date=2011&rft.relation=https://cs.anu.edu.au/techreports/2011/TR-CS-11-02.pdf&rft_subject=Image Processing&rft_subject=Information and Computing Sciences&rft_subject=Artificial Intelligence and Image Processing&rft_subject=Computer Vision&rft.type=dataset&rft.language=English Access the data
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