Abstract
Humans attribute meaning to actions, and can recognize, imitate, predict, compose from parts, and analyse complex actions performed by other humans. We have built a model of action representation and understanding which takes as input perceptual data of humans performing manipulatory actions and finds a semantic interpretation of it. It achieves this by representing actions as minimal plans based on a few primitives. The motivation for our approach is to have a description, that abstracts away the variations in the way humans perform actions. The model can be used to represent complex activities on the basis of simple actions. The primitives of these minimal plans are embodied in the physicality of the system doing the analysis. The model understands an action under observation by recognising which plan is occurring. Using primitives thus rooted in its own physical structure, the model has a semanticist and causal understanding of what it observes. Using plans, the model considers actions as well as complex activities in terms of causality, compositions, and goal achievement, enabling it to perform complex tasks like prediction of primitives, separation of interleaved actions and filtering of perceptual input. We use our model over an action dataset involving humans using hand tools on objects in a constrained universe to understand an activity it has not seen before in terms of actions whose plans it knows of. The model thus illustrates a novel approach of understanding human actions by a robot.
| Original language | English (US) |
|---|---|
| Title of host publication | IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems |
| Pages | 5908-5914 |
| Number of pages | 7 |
| DOIs | |
| State | Published - 2013 |
| Externally published | Yes |
| Event | 2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 - Tokyo, Japan Duration: Nov 3 2013 → Nov 8 2013 |
Other
| Other | 2013 26th IEEE/RSJ International Conference on Intelligent Robots and Systems: New Horizon, IROS 2013 |
|---|---|
| Country | Japan |
| City | Tokyo |
| Period | 11/3/13 → 11/8/13 |
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ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Computer Vision and Pattern Recognition
- Computer Science Applications
Cite this
Minimalist plans for interpreting manipulation actions. / Guha, Anupam; Yang, Yezhou; Fermuuller, Cornelia; Aloimonos, Yiannis.
IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems. 2013. p. 5908-5914 6697213.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Minimalist plans for interpreting manipulation actions
AU - Guha, Anupam
AU - Yang, Yezhou
AU - Fermuuller, Cornelia
AU - Aloimonos, Yiannis
PY - 2013
Y1 - 2013
N2 - Humans attribute meaning to actions, and can recognize, imitate, predict, compose from parts, and analyse complex actions performed by other humans. We have built a model of action representation and understanding which takes as input perceptual data of humans performing manipulatory actions and finds a semantic interpretation of it. It achieves this by representing actions as minimal plans based on a few primitives. The motivation for our approach is to have a description, that abstracts away the variations in the way humans perform actions. The model can be used to represent complex activities on the basis of simple actions. The primitives of these minimal plans are embodied in the physicality of the system doing the analysis. The model understands an action under observation by recognising which plan is occurring. Using primitives thus rooted in its own physical structure, the model has a semanticist and causal understanding of what it observes. Using plans, the model considers actions as well as complex activities in terms of causality, compositions, and goal achievement, enabling it to perform complex tasks like prediction of primitives, separation of interleaved actions and filtering of perceptual input. We use our model over an action dataset involving humans using hand tools on objects in a constrained universe to understand an activity it has not seen before in terms of actions whose plans it knows of. The model thus illustrates a novel approach of understanding human actions by a robot.
AB - Humans attribute meaning to actions, and can recognize, imitate, predict, compose from parts, and analyse complex actions performed by other humans. We have built a model of action representation and understanding which takes as input perceptual data of humans performing manipulatory actions and finds a semantic interpretation of it. It achieves this by representing actions as minimal plans based on a few primitives. The motivation for our approach is to have a description, that abstracts away the variations in the way humans perform actions. The model can be used to represent complex activities on the basis of simple actions. The primitives of these minimal plans are embodied in the physicality of the system doing the analysis. The model understands an action under observation by recognising which plan is occurring. Using primitives thus rooted in its own physical structure, the model has a semanticist and causal understanding of what it observes. Using plans, the model considers actions as well as complex activities in terms of causality, compositions, and goal achievement, enabling it to perform complex tasks like prediction of primitives, separation of interleaved actions and filtering of perceptual input. We use our model over an action dataset involving humans using hand tools on objects in a constrained universe to understand an activity it has not seen before in terms of actions whose plans it knows of. The model thus illustrates a novel approach of understanding human actions by a robot.
UR - http://www.scopus.com/inward/record.url?scp=84893751243&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893751243&partnerID=8YFLogxK
U2 - 10.1109/IROS.2013.6697213
DO - 10.1109/IROS.2013.6697213
M3 - Conference contribution
AN - SCOPUS:84893751243
SN - 9781467363587
SP - 5908
EP - 5914
BT - IROS 2013: New Horizon, Conference Digest - 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems
ER -