Image-MLの皆様， マルチメディア技術を用いた食事管理 に関するワークショップ 8th International Workshop on Multimedia Assisted Dietary Management (MADiMa) の 論文募集のご案内をお送り致します． インドのコルカタで 12/1-5 に開催されるICPR の workshop として 開催予定です．Workshopは 12/1 に開催予定です． 食事画像の認識・生成や応用アプリ，クロスモーダルレシピ検索, LLMやLMMの 食事への応用など，食事に関する様々なトピックが対象となっています． 論文締切は 8月30日となっています． 詳しくは，以下のCFP および https://www.madima.org/ を御覧ください． 以上，よろしくお願い致します． 電通大 柳井 =================================================== Call For Papers (apologies for multiple copies) =================================================== The 9th International Workshop on Multimedia Assisted Dietary Management (MADiMa2024) is organized in conjunction with the 27th International Conference on Pattern Recognition (ICPR2024). Website: www.madima.org Place: Kolkata, India Date: 1st December 2024 Submission Deadline: 30th August 2024 RATIONALE ========= Recent advancements in artificial intelligence, wearable technologies, big data analytics, and healthcare technology in general have ushered in the era of mHealth, revolutionizing healthcare services. This transformation is not only reshaping the way we approach healthcare but also paving the way for personalized nutrition, healthier lifestyles to prevent diseases and achieve effective self-management of chronic conditions. A significant challenge in nutrition research is acquiring high-quality, precise nutrition information in an economically viable manner. Mobile and wearable technologies, with their flexibility and efficiency, coupled with the capabilities of artificial intelligence enable the analysis of large volumes of multi-level and heterogeneous data, pattern detection, risk prediction, and intervention guidance. This fusion holds immense potential for promoting healthier dietary habits and behaviors and facilitating communication between caregivers and care recipients. The need for accurate, automatic, real-time, and personalised dietary advice has been recently complemented by advances in artificial intelligence and computer vision, permitting the development of end-to-end pipelines for food content analysis. 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 and recipe databases and may 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 monitoring, assessment, and management. SCOPE ===== The main scope of MADiMa2024 is 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, assessment, and management of food intake. The combined use of multimedia, machine learning algorithms, ubiquitous computing and mobile technologies permits 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 and demonstrate 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: - Supervised food recognition (Fine-grained/Transfer/Noisy-label Learning) - Unsupervised food recognition (Self-supervised/Multi-modal Learning) - Out-of-distribution food detection (Anomaly Detection, Open-Set Learning) - Food image synthesis with generative models (GANs, Diffusion Models, etc.) - Food detection and segmentation (vision foundation models, SAM, etc.) - LLMs/LVMs to automatize food composition analysis (recipe comprehension, database reading, nutritional content estimation, etc.) - Monocular/Binocular depth estimation from mobile/static sensors - 3D point cloud processing and analysis for food volume estimation - Augmented/Virtual reality for food analysis and portion estimation - Benchmarks, evaluation protocols, and metrics for the above topics IMPORTANT DATES ================ - Paper submission deadline: August 30th, 2024 - Notification of acceptance: September 20th, 2024 - Camera ready deadline: September 26th, 2024 KEYNOTE SPEAKERS ================= - Prof. Ramesh Jain, University of California, Irvine (CONFIRMED) Topic: Conversational Personal Food Agents - Prof. Georges Dedousis, Harokopio University of Athens (CONFIRMED) Topic: The Importance of Multimodal Data Analysis in Obesity Prevention and Management - Prof. Dima Damen, University of Bristol and Google DeepMind (TENTATIVE) WORKSHOP CHAIRS ================= - Stavroula Mougiakakou, University of Bern, Switzerland - Keiji Yanai, The University of Electro-Communications, Tokyo, Japan - Dario Allegra, University of Catania, Italy - Yoko Yamakata, The University of Tokyo, Japan - Lorenzo Brigato, University of Bern, Switzerland For more information, please visit the workshop's website at www.madima.org. The workshop chairs, Stavroula Mougiakakou Keiji Yanai Dario Allegra Yoko Yamakata Lorenzo Brigato