Manifold Learning and Recognition of Human Activity Using Body-Area Sensors
Published: Dec 1, 2011
Abstract
Manifold learning is an important technique for effective nonlinear dimensionality reduction in machine learning. In this paper, we present a manifold-based framework for human activity recognition using wearable motion sensors. In our framework, we use locally linear embedding (LLE) to capture the intrinsic structure and build nonlinear manifolds for each activity. A nearest-neighbor interpolation technique is then applied to learn the mapping...
Paper Details
Title
Manifold Learning and Recognition of Human Activity Using Body-Area Sensors
Published Date
Dec 1, 2011
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