Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Bock, Marius"'
As wearable-based data annotation remains, to date, a tedious, time-consuming task requiring researchers to dedicate substantial time, benchmark datasets within the field of Human Activity Recognition in lack richness and size compared to datasets av
Externí odkaz:
http://arxiv.org/abs/2408.05169
As of today, state-of-the-art activity recognition from wearable sensors relies on algorithms being trained to classify fixed windows of data. In contrast, video-based Human Activity Recognition, known as Temporal Action Localization (TAL), has follo
Externí odkaz:
http://arxiv.org/abs/2311.15831
Publikováno v:
MDPI Sensors, 25 June 2023, Special Issue Inertial Measurement Units in Sport
We present a benchmark dataset for evaluating physical human activity recognition methods from wrist-worn sensors, for the specific setting of basketball training, drills, and games. Basketball activities lend themselves well for measurement by wrist
Externí odkaz:
http://arxiv.org/abs/2305.13124
Research has shown the complementarity of camera- and inertial-based data for modeling human activities, yet datasets with both egocentric video and inertial-based sensor data remain scarce. In this paper, we introduce WEAR, an outdoor sports dataset
Externí odkaz:
http://arxiv.org/abs/2304.05088
Activity recognition systems that are capable of estimating human activities from wearable inertial sensors have come a long way in the past decades. Not only have state-of-the-art methods moved away from feature engineering and have fully adopted en
Externí odkaz:
http://arxiv.org/abs/2110.06663
Recent studies in Human Activity Recognition (HAR) have shown that Deep Learning methods are able to outperform classical Machine Learning algorithms. One popular Deep Learning architecture in HAR is the DeepConvLSTM. In this paper we propose to alte
Externí odkaz:
http://arxiv.org/abs/2108.00702