Now, a software that can judge mood through your photos
LONDON: A new 'mood-judging' software developed by an Indian-origin scientist can pick out the happiest snaps from a wedding or help you choose gleeful photos for your Facebook profile.
The software by Abhinav Dhall at the Australian National University in Canberra and colleagues analyses all the faces in a photo to give the shot an overall "mood score".
The team used face tracking software to analyse the smiles of the faces in a group by noting the positions of nine spots on the face such as the corners of the mouth and eyes.
A machine learning algorithm, trained on photos that had been pre-labelled by humans, then used this data to give each face a smile intensity score, 'New Scientist' reported.
The team also programmed the system to incorporate information from volunteers, who assessed how important the intensity of any individual's smile was to the overall mood score of a photo.
Those who were standing near the centre of a picture were given a stronger weighting, for example, while partially obscured faces were less influential.
When asked to gauge the happiness level of a photo, the system only deviated from the opinion of a human by around 7 per cent.
Dhall said the aim is to be able to assess the overall mood of a group from a single shot. By looking at a sequence of frames in a video, it could even gauge the mood of a crowd in real time.
"If the mood score goes down over the time, we can assume that the group are getting angry. It could also be used to view albums on Facebook by arranging photos so the happiest ones are shown first, for example," said Dhall.
LONDON: A new 'mood-judging' software developed by an Indian-origin scientist can pick out the happiest snaps from a wedding or help you choose gleeful photos for your Facebook profile.
The software by Abhinav Dhall at the Australian National University in Canberra and colleagues analyses all the faces in a photo to give the shot an overall "mood score".
The team used face tracking software to analyse the smiles of the faces in a group by noting the positions of nine spots on the face such as the corners of the mouth and eyes.
A machine learning algorithm, trained on photos that had been pre-labelled by humans, then used this data to give each face a smile intensity score, 'New Scientist' reported.
The team also programmed the system to incorporate information from volunteers, who assessed how important the intensity of any individual's smile was to the overall mood score of a photo.
Those who were standing near the centre of a picture were given a stronger weighting, for example, while partially obscured faces were less influential.
When asked to gauge the happiness level of a photo, the system only deviated from the opinion of a human by around 7 per cent.
Dhall said the aim is to be able to assess the overall mood of a group from a single shot. By looking at a sequence of frames in a video, it could even gauge the mood of a crowd in real time.
"If the mood score goes down over the time, we can assume that the group are getting angry. It could also be used to view albums on Facebook by arranging photos so the happiest ones are shown first, for example," said Dhall.
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