Cross-Domain Activity Recognition

In activity recognition, one major challenge is huge manual effort in labeling when a new domain of activities is to be tested. In this paper, the authors ask an interesting question: can the people transfer the available labeled data from a set of existing activities in one domain to help recognize the activities in another different but related domain? The people answer is "Yes", provided that the sensor data from the two domains are related in some way. They develop a bridge between the activities in two domains by learning a similarity function via Web search, under the condition that the sensor data are from the same feature space.