Abstract
Goal and plan recognition of daily living activities has attracted much interest due to its applicability to ambient assisted living. Such applications require the automatic recognition of high-level activities based on multiple steps performed by human beings in an environment. In this work, we address the problem of plan and goal recognition of human activities in an indoor environment. Unlike existing approaches that use only actions to identify the goal, we use objects and their relations to identify the plan and goal towards which the subject in the video is pursuing. Our approach combines state-of-the-art object and relationship detection to analyze raw video data with a goal recognition algorithm to identify the subject’s ultimate goal in the video. Experiments show that our approach identifies cooking activities in a kitchen scenario.
Original language | English |
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Title of host publication | Advances in Soft Computing |
Subtitle of host publication | 19th Mexican International Conference on Artificial Intelligence, MICAI 2020 Mexico Cit, Mexico, October 12-17, 2020 Proceedings, Part 1 |
Editors | Lourdes Martínez-Villaseñor, Oscar Herrera-Alcántara, Hiram Ponce, Félix A. Castro-Espinoza |
Place of Publication | Cham, Switzerland |
Publisher | Springer |
Pages | 325-337 |
Number of pages | 13 |
ISBN (Electronic) | 978-3-030-60884-2 |
ISBN (Print) | 978-3-030-60883-5 |
DOIs | |
Publication status | Published - 7 Oct 2020 |
Event | 19th Mexican International Conference on Artificial Intelligence - Mexico City, Mexico Duration: 12 Oct 2020 → 17 Oct 2020 http://micai.org/2020/ |
Publication series
Name | Lecture Notes in Artificial Intelligence |
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Publisher | Springer |
Volume | 12468 |
ISSN (Print) | 2945-9133 |
ISSN (Electronic) | 2945-9141 |
Conference
Conference | 19th Mexican International Conference on Artificial Intelligence |
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Abbreviated title | MICAI 2020 |
Country/Territory | Mexico |
City | Mexico City |
Period | 12/10/20 → 17/10/20 |
Internet address |
Keywords
- goal recognition
- relationship detection
- object detection