Knowledge-driven Egocentric Multimodal Activity Recognition
时间: 2024-06-06 22:07:13 浏览: 25
Knowledge-driven egocentric multimodal activity recognition refers to a type of activity recognition that uses both visual and non-visual cues to identify and classify human activities in first-person point of view videos. It is a knowledge-driven approach that combines prior knowledge about the context of the activity and the user's behavior to improve the accuracy of activity recognition.
This approach uses multiple modalities, including visual features such as images and videos, audio signals, and sensor data from wearable devices such as accelerometers and gyroscopes. By combining these different types of data, the system can identify patterns and features that are unique to each activity.
The knowledge-driven aspect of this approach involves using prior knowledge about the context of the activity and the user's behavior to improve the accuracy of activity recognition. For example, if the user is cooking in the kitchen, the system can use prior knowledge about the types of activities that typically occur in the kitchen, such as chopping vegetables or washing dishes, to help identify the current activity.
Overall, knowledge-driven egocentric multimodal activity recognition is a promising approach for accurately identifying and classifying human activities in first-person point of view videos. It has potential applications in a variety of fields, including healthcare, sports, and entertainment.
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