Scope and Aims

Recent advancement of technology enables installations of small sized accelerometers or gyroscopes on various kinds of wearable/portable information devices. By using such wearable sensors, these devices can estimate its posture or status. However, most of current devices only utilize these sensors for simple orientation and gesture recognition. More deep understandings and recognition of human activity through these sensors will enable the next-generation human-oriented computing. To enable the real-world application by these kinds of wearable sensors, a large scale human activity corpus might play an important role. Additionally, we have now a lot of high-performance mobile devices in real-world such as smart-phones. It is a great challenge to utilize such enormous number of wearable sensors to collect large-scale activity corpus. In recent years, there are several on-going projects which are collecting human activities. In this workshop, we are planning to share these experiences of current research on human activity corpus and its applications among the researchers and the practitioners and to have a deep discussion for future of activity sensing.

Areas of Interest

• Human Activity Sensing Corpus
• Large Scale Data Collection
• Data Validation
• Data Tagging / Labeling
• Efficient Data Collection
• Data Mining from Corpus
• Automatic Segmentation
• Performance Evaluation
• Man-machine Interaction
• Noise Robustness
• Non Supervised Machine Learning
• Sensor Data Fusion
• Tools for Human Activity Corpus/Sensing
• Participatory Sensing
• Feature Extraction and Selection
• Context Awareness
• Pedestrian Navigation
• Social Activities Analysis/Detection
• Compressive Sensing
• Sensing Devices
• Lifelog Systems
• Route Recognition/Detection
• Wearable Application
• Gait Analysis
• Health-care Monitoring/Recommendation
• Daily-life Worker Support

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