To extend the HIMO dataset to include more diverse object types, such as large furniture or articulated objects, several strategies can be employed. First, the dataset can incorporate a wider range of object categories by selecting items from various environments, including living rooms, offices, and outdoor settings. This would involve identifying and 3D scanning large furniture pieces like chairs, tables, and cabinets, as well as articulated objects such as tools or toys that require complex interactions.
Second, the data acquisition process would need to adapt to the unique challenges posed by larger objects. For instance, the optical MoCap system may require additional cameras or a different setup to capture the full range of motion around larger items. Furthermore, articulated objects may necessitate the use of advanced tracking techniques to accurately capture their movements and interactions with human subjects.
Third, the annotation process should be expanded to include detailed descriptions of interactions with these new object types, ensuring that the fine-grained textual descriptions and temporal segments remain consistent with the existing dataset. This would enhance the dataset's utility for training models on human-object interactions involving a broader spectrum of objects, ultimately improving the generalization capabilities of the synthesized interactions.