Name
Title | ||
|---|---|---|
Toward Practical Activity Recognition: Recognizing Complex Activities With Wide Variations |
Abstract | ||
|---|---|---|
Most activity classifiers focus on recognizing application-specific activities that are mostly performed in a scripted manner, where there is very little room for variation within the activity. These classifiers are mainly good at recognizing short scripted activities that are performed in a specific way.In reality, especially when considering daily activities, humans perform complex activities in a variety of ways. In this work, we aim to make activity recognition more practical by proposing a novel approach to recognize complex heterogeneous activities that. could be performed in a wide variety of ways. We collect. data from 15 subjects performing 8 complex activities and test our approach while analyzing it from different aspects. The results show the validity of our approach. They also show how it performs better than the state-of-the-art approaches that tried to recognize the same activities in a more controlled environment. |
Year | Venue | Field |
|---|---|---|
2018 | 2018 IEEE INTERNATIONAL CONFERENCE ON PERVASIVE COMPUTING AND COMMUNICATIONS WORKSHOPS (PERCOM WORKSHOPS) | Activity recognition,Activities of daily living,Computer science,Human–computer interaction,Distributed computing |
DocType | ISSN | Citations |
Conference | 2474-2503 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rabih Younes | 1 | 1 | 0.73 |
| Mark T. Jones | 2 | 261 | 46.58 |
| Thomas L. Martin | 3 | 201 | 24.17 |