A wearable human behavior activity recognition method based on hash space optimization
By constructing a compact hash feature representation and introducing MMD and self-updating center loss optimization mechanisms, the problems of insufficient class separation and loose intra-class distribution in human activity recognition by hash methods are solved, thereby improving recognition accuracy and robustness and making it suitable for resource-constrained wearable devices.
CN120910602BActive Publication Date: 2026-06-26NANTONG UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NANTONG UNIV
- Filing Date
- 2025-06-16
- Publication Date
- 2026-06-26
Smart Images
Figure CN120910602B_ABST
Abstract
The application discloses a kind of based on hash space optimization wearable human behavior activity identification method, belong to human activity identification technical field, solve the problem of high behavior recognition calculation complexity, low processing efficiency in wearable device.Its technical scheme is as follows: including the following steps: S1, data preprocessing;S2, feature extraction and hash embedding;S3, MMD optimization;S4, center optimization;S5, loss calculation;S6, classification prediction.The beneficial effects of the application are that the method has the advantages of compact feature expression, high classification efficiency and excellent recognition accuracy, and is suitable for wearable devices such as smart bands and smart watches, and has a wide range of practical application prospects.
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