Finally, help is at hand for those trying to lose weight but do not want to spend money consulting trained nutritionists or are too busy to go through self-help books.
Computer scientists at the Harvard School of Engineering and Applied Sciences (SEAS) have developed a tool that lets you snap a photo of your meal and let the crowd estimates its nutritional value.
PlateMate's calorie estimates have proved, in tests, to be just as accurate as those of trained nutritionists, and more accurate than the users' own logs.
"We can take things that used to require experts and do them with crowds," said Jon Noronha, who co-developed PlateMate as an undergraduate at Harvard and now works at Microsoft.
"Estimating the nutritional value of a meal is a fairly complex task, from a computational standpoint, but with a structured workflow and some cultural awareness, we've expanded what crowdsourcing can achieve," stated Noronha.
Often, individuals who claim they are trying to lose weight will underestimate their caloric intake, so PlateMate's advantage is that it allows the user to quickly consult impartial observers, without having to pay for the advice and supervision of an expert nutritionist.
Reproducing the accuracy of an expert in a crowd of untrained strangers, however, was not straightforward.
PlateMate works in coordination with Amazon Mechanical Turk, a system originally intended to help improve product listings on Amazon.com.
Turkers, as the crowd workers call themselves, receive a few cents for each puzzle-like task they complete.
PlateMate divides nutrition analysis into several iterative tasks, asking groups of Turkers to distinguish between foods in the photo, identify what they are, and estimate quantities.
The nutrition totals for the meal are then automatically calculated.
The research was presented at the 24th ACM Symposium on User Interface Software and Technology, a leading conference on human-computer interaction.