Search Results for author: Thomas Plötz

Found 7 papers, 2 papers with code

Generating Virtual On-body Accelerometer Data from Virtual Textual Descriptions for Human Activity Recognition

1 code implementation4 May 2023 Zikang Leng, Hyeokhyen Kwon, Thomas Plötz

We benchmarked our approach on three HAR datasets (RealWorld, PAMAP2, and USC-HAD) and demonstrate that the use of virtual IMU training data generated using our new approach leads to significantly improved HAR model performance compared to only using real IMU data.

Human Activity Recognition Motion Synthesis

IMUGPT 2.0: Language-Based Cross Modality Transfer for Sensor-Based Human Activity Recognition

1 code implementation1 Feb 2024 Zikang Leng, Amitrajit Bhattacharjee, Hrudhai Rajasekhar, Lizhe Zhang, Elizabeth Bruda, Hyeokhyen Kwon, Thomas Plötz

With the emergence of generative AI models such as large language models (LLMs) and text-driven motion synthesis models, language has become a promising source data modality as well as shown in proof of concepts such as IMUGPT.

Human Activity Recognition Motion Synthesis

Towards Using Unlabeled Data in a Sparse-coding Framework for Human Activity Recognition

no code implementations25 Dec 2013 Sourav Bhattacharya, Petteri Nurmi, Nils Hammerla, Thomas Plötz

We propose a sparse-coding framework for activity recognition in ubiquitous and mobile computing that alleviates two fundamental problems of current supervised learning approaches.

Human Activity Recognition

Assessing the State of Self-Supervised Human Activity Recognition using Wearables

no code implementations22 Feb 2022 Harish Haresamudram, Irfan Essa, Thomas Plötz

As such, self-supervision, i. e., the paradigm of 'pretrain-then-finetune' has the potential to become a strong alternative to the predominant end-to-end training approaches, let alone hand-crafted features for the classic activity recognition chain.

Domain Adaptation Human Activity Recognition +1

Fine-grained Human Activity Recognition Using Virtual On-body Acceleration Data

no code implementations2 Nov 2022 Zikang Leng, Yash Jain, Hyeokhyen Kwon, Thomas Plötz

In this work we first introduce a measure to quantitatively assess the subtlety of human movements that are underlying activities of interest--the motion subtlety index (MSI)--which captures local pixel movements and pose changes in the vicinity of target virtual sensor locations, and correlate it to the eventual activity recognition accuracy.

Human Activity Recognition

On the Benefit of Generative Foundation Models for Human Activity Recognition

no code implementations18 Oct 2023 Zikang Leng, Hyeokhyen Kwon, Thomas Plötz

In human activity recognition (HAR), the limited availability of annotated data presents a significant challenge.

Human Activity Recognition Motion Synthesis

Know Thy Neighbors: A Graph Based Approach for Effective Sensor-Based Human Activity Recognition in Smart Homes

no code implementations16 Nov 2023 Srivatsa P, Thomas Plötz

To overcome this limitation, we propose a novel graph-guided neural network approach that performs activity recognition by learning explicit co-firing relationships between sensors.

Human Activity Recognition

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