Thank you!

Thanks to all authors, committee members, reviewers and participants who helped make MADiMa2015 a success! We hope to see you again in the next MADiMa workshop.

 

Rationale

The prevention of onset and progression of diet-related acute and chronic diseases (e.g. diabetes, obesity, cardiovascular diseases and cancer) requires reliable and intuitive dietary management. The need for accurate, automatic, real-time and personalized dietary advice has been recently complemented by the advances in computer vision and smartphone technologies, permitting the development of the first mobile food multimedia content analysis applications. The proposed solutions rely on the analysis of multimedia content captured by wearable sensors, smartphone cameras, barcode scanners, RFID readers and IR sensors, along with already established nutritional databases and often require some user input. In the field of nutritional management, multimedia not only bridges diverse information and communication technologies, but also computer science with medicine, nutrition and dietetics. This confluence brings new challenges and opportunities on dietary management.

Scope

MADiMa2015 aims to bring together researchers from the diverse fields of engineering, computer science and nutrition who investigate the use of information and communication technologies for better monitoring and management of food intake. The combined use of multimedia, machine learning algorithms, ubiquitous computing and mobile technologies permit the development of applications and systems able to monitor the dietary behavior, analyze food intake, identify eating patterns and provide feedback to the user towards healthier nutrition. The researchers will present their latest progress and discuss novel ideas in the field. Besides the technologies used, emphasis will be given to the precise problem definition, the available nutritional databases, the need for benchmarking multimedia databases of packed and unpacked food and the evaluation protocols.

Topics

Topics of interest include (but are not limited to) the following:

  • Ubiquitous and mobile computing for dietary assessment
  • Computer vision for food detection, segmentation and recognition
  • 3D reconstruction for food portion estimation
  • Augmented reality for food portion estimation
  • Wearable sensors for food intake detection
  • Computerized food composition (nutrients, allergens) analysis
  • Multimedia technologies for eating monitoring
  • Smartphone technologies for dietary behavioral patterns
  • Food multimedia databases
  • Evaluation protocols of dietary management systems
  • Multimedia assisted self-management of health and disease