| 1. |
|
|
| 2. |
- Hemeren, Paul, et al.
(författare)
-
Similarity Judgments of Hand-Based Actions : From Human Perception to a Computational Model
- 2019
-
Ingår i: 42nd European Conference on Visual Perception (ECVP) 2019 Leuven. - : Sage Publications. ; , s. 79-79
-
Konferensbidrag (refereegranskat)abstract
- How do humans perceive actions in relation to other similar actions? How can we develop artificial systems that can mirror this ability? This research uses human similarity judgments of point-light actions to evaluate the output from different visual computing algorithms for motion understanding, based on movement, spatial features, motion velocity, and curvature. The aim of the research is twofold: (a) to devise algorithms for motion segmentation into action primitives, which can then be used to build hierarchical representations for estimating action similarity and (b) to develop a better understanding of human actioncategorization in relation to judging action similarity. The long-term goal of the work is to allow an artificial system to recognize similar classes of actions, also across different viewpoints. To this purpose, computational methods for visual action classification are used and then compared with human classification via similarity judgments. Confusion matrices for similarity judgments from these comparisons are assessed for all possible pairs of actions. The preliminary results show some overlap between the outcomes of the two analyses. We discuss the extent of the consistency of the different algorithms with human action categorization as a way to model action perception.
|
|
| 3. |
- Metta, Giorgio, et al.
(författare)
-
The iCub humanoid robot : An open-systems platform for research in cognitive development
- 2010
-
Ingår i: Neural Networks. - : Elsevier BV. - 0893-6080 .- 1879-2782. ; 23:8-9, s. 1125-1134
-
Tidskriftsartikel (refereegranskat)abstract
- We describe a humanoid robot platform - the iCub - which was designed to support collaborative research in cognitive development through autonomous exploration and social interaction. The motivation for this effort is the conviction that significantly greater impact can be leveraged by adopting an open systems policy for software and hardware development. This creates the need for a robust humanoid robot that offers rich perceptuo-motor capabilities with many degrees of freedom, a cognitive capacity for learning and development, a software architecture that encourages reuse & easy integration, and a support infrastructure that fosters collaboration and sharing of resources. The iCub satisfies all of these needs in the guise of an open-system platform which is freely available and which has attracted a growing community of users and developers. To date, twenty iCubs each comprising approximately 5000 mechanical and electrical parts have been delivered to several research labs in Europe and to one in the USA.
|
|
| 4. |
- Nair, Vipul, et al.
(författare)
-
Action similarity judgment based on kinematic primitives
- 2020
-
Ingår i: 2020 Joint IEEE 10th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob). - : IEEE. - 9781728173061 - 9781728173207
-
Konferensbidrag (refereegranskat)abstract
- Understanding which features humans rely on - in visually recognizing action similarity is a crucial step towards a clearer picture of human action perception from a learning and developmental perspective. In the present work, we investigate to which extent a computational model based on kinematics can determine action similarity and how its performance relates to human similarity judgments of the same actions. To this aim, twelve participants perform an action similarity task, and their performances are compared to that of a computational model solving the same task. The chosen model has its roots in developmental robotics and performs action classification based on learned kinematic primitives. The comparative experiment results show that both the model and human participants can reliably identify whether two actions are the same or not. However, the model produces more false hits and has a greater selection bias than human participants. A possible reason for this is the particular sensitivity of the model towards kinematic primitives of the presented actions. In a second experiment, human participants' performance on an action identification task indicated that they relied solely on kinematic information rather than on action semantics. The results show that both the model and human performance are highly accurate in an action similarity task based on kinematic-level features, which can provide an essential basis for classifying human actions.
|
|
| 5. |
- Nair, Vipul, et al.
(författare)
-
Kinematic primitives in action similarity judgments : A human-centered computational model
- 2023
-
Ingår i: IEEE Transactions on Cognitive and Developmental Systems. - : IEEE. - 2379-8920 .- 2379-8939. ; 15:4, s. 1981-1992
-
Tidskriftsartikel (refereegranskat)abstract
- This paper investigates the role that kinematic features play in human action similarity judgments. The results of three experiments with human participants are compared with the computational model that solves the same task. The chosen model has its roots in developmental robotics and performs action classification based on learned kinematic primitives. The comparative experimental results show that both model and human participants can reliably identify whether two actions are the same or not. Specifically, most of the given actions could be similarity judged based on very limited information from a single feature domain (velocity or spatial). Both velocity and spatial features were however necessary to reach a level of human performance on evaluated actions. The experimental results also show that human performance on an action identification task indicated that they clearly relied on kinematic information rather than on action semantics. The results show that both the model and human performance are highly accurate in an action similarity task based on kinematic-level features, which can provide an essential basis for classifying human actions.
|
|
| 6. |
|
|
| 7. |
|
|
