Abstract

MART (Micro-activity Retrieval Task) was a NTCIR-15 collaborative benchmarking pilot task. The NTCIR-15 MART pilot aimed to motivate the development of first generation techniques for high-precision micro-activity detection and retrieval, to support the identification and retrieval of activities that occur over short time-scales such as minutes, rather than the long-duration event segmentation tasks of the past work. Participating researchers developed and benchmarked approaches to retrieve micro-activities from rich time-aligned multi-modal sensor data. Groups were ranked in decreasing order of micro-activity retrieval accuracy using mAP (mean Average Precision). The dataset used for the task consisted of a detailed lifelog of activities gathered using a controlled protocol of real-world activities (e.g. using a computer, eating, daydreaming, etc). The data included a lifelog camera data stream, biosignal activity (EOG, HR), and computer interactions (mouse movements, screenshots, etc). This task presented a novel set of challenging micro-activity based topics.