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Publications (10 of 29) Show all publications
Hemeren, P. (2019). Reverse Hierarchy Theory and the Role of Kinematic Information in Semantic Level Processing and Intention Perception. In: : . Paper presented at Anticipation and Anticipatory Systems: Humans Meet Artificial Intelligence, Örebro, Sweden, June 10-13, 2019.
Open this publication in new window or tab >>Reverse Hierarchy Theory and the Role of Kinematic Information in Semantic Level Processing and Intention Perception
2019 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

In many ways, human cognition is importantly predictive (e.g., Clark, 2015). A critical source of information that humans use to anticipate the future actions of other humans and to perceive intentions is bodily movement (e.g., Ansuini et al., 2014; Becchio et al., 2018; Koul et al., 2019; Sciutti et al., 2015). This ability extends to perceiving the intentions of other humans based on past and current actions. The purpose of this abstract is to address the issue of anticipation according to levels of processing in visual perception and experimental results that demonstrate high-level semantic processing in the visual perception of various biological motion displays. These research results (Hemeren & Thill, 2011; Hemeren et al., 2018; Hemeren et al., 2016) show that social aspects and future movement patterns can be predicted from fairly simple kinematic patterns in biological motion sequences, which demonstrates the different environmental (gravity and perspective) and bodily constraints that contribute to understanding our social and movement-based interactions with others. Understanding how humans perceive anticipation and intention amongst one another should help us create artificial systems that also can perceive human anticipation and intention.

Keywords
anticipation, intention perception, biological motion, cognitive systems
National Category
Human Computer Interaction
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-17826 (URN)
Conference
Anticipation and Anticipatory Systems: Humans Meet Artificial Intelligence, Örebro, Sweden, June 10-13, 2019
Funder
Knowledge Foundation
Available from: 2019-10-28 Created: 2019-10-28 Last updated: 2019-10-30Bibliographically approved
Hemeren, P., Nair, V., Nicora, E., Vignolo, A., Noceti, N., Odone, F., . . . Sciutti, A. (2019). Similarity Judgments of Hand-Based Actions: From Human Perception to a Computational Model. In: 42nd European Conference on Visual Perception (ECVP) 2019 Leuven: . Paper presented at 42nd European Conference on Visual Perception (ECVP) Leuven, Belgium, August 25-29, 2019 (pp. 79-79). Sage Publications, 48
Open this publication in new window or tab >>Similarity Judgments of Hand-Based Actions: From Human Perception to a Computational Model
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2019 (English)In: 42nd European Conference on Visual Perception (ECVP) 2019 Leuven, Sage Publications, 2019, Vol. 48, p. 79-79Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

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.

Place, publisher, year, edition, pages
Sage Publications, 2019
Series
Perception, ISSN 0301-0066, E-ISSN 1468-4233 ; 48
Keywords
biological motion, action primitives, artificial systems
National Category
Applied Psychology
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-17831 (URN)10.1177/0301006619863862 (DOI)
Conference
42nd European Conference on Visual Perception (ECVP) Leuven, Belgium, August 25-29, 2019
Available from: 2019-10-29 Created: 2019-10-29 Last updated: 2019-11-06Bibliographically approved
Hemeren, P. & Nair, V. (2018). Actions, intentions and environmental constraints in biological motion perception. In: Thomas Hünefeldt, Marta Olivetti Belardinelli (Ed.), Spatial Cognition in a Multimedia and Intercultural World: Proceedings of the 7th International Conference on Spatial Cognition (ICSC 2018). Paper presented at 7th International Conference on Spatial Cognition (ICSC 2018), Rome, Italy, September 10-14, 2018 (pp. S8-S8). Springer, 19 (Suppl 1)
Open this publication in new window or tab >>Actions, intentions and environmental constraints in biological motion perception
2018 (English)In: Spatial Cognition in a Multimedia and Intercultural World: Proceedings of the 7th International Conference on Spatial Cognition (ICSC 2018) / [ed] Thomas Hünefeldt, Marta Olivetti Belardinelli, Springer, 2018, Vol. 19 (Suppl 1), p. S8-S8Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

In many ways, human cognition is importantly predictive. We predict the sensory consequences of our own actions, but we also predict, and react to, the sensory consequences of how others experience their own actions. This ability extends to perceiving the intentions of other humans based on past and current actions. We present research results that show that social aspects and future movement patterns can be predicted from fairly simple kinematic patterns in biological motion sequences. The purpose of this presentation is to demonstrate and discuss the different environmental (gravity and perspective) and bodily constraints on understanding our social and movement-based interactions with others. In a series of experiments, we have used psychophysical methods and recordings from interactions with objects in natural settings. This includes experiments on the incidental processing of biological motion as well as driving simulator studies that examine the role of kinematic patterns of cyclists and driver’s accuracy to predict the cyclist’s intentions in traffic.  The results we present show both clear effects of “low-level” biological motion factors, such as opponent motion, on the incidental triggering of attention in basic perceptual tasks and “higher-lever” top-down guided perception in the intention prediction of cyclist behavior. We propose to use our results to stimulate discussion about the interplay between expectation mediated and stimulus driven effects of visual processing in spatial cognition the context of human interaction. Such discussion will include the role of context in gesture recognition and to what extent our visual system can handle visually complex environments.

Place, publisher, year, edition, pages
Springer, 2018
Series
Cognitive Processing, ISSN 1612-4782, E-ISSN 1612-4790
Keywords
biological motion, intention recognition, attention, social cognition
National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-16357 (URN)10.1007/s10339-018-0884-3 (DOI)
Conference
7th International Conference on Spatial Cognition (ICSC 2018), Rome, Italy, September 10-14, 2018
Funder
Knowledge Foundation, 20140220
Available from: 2018-11-03 Created: 2018-11-03 Last updated: 2018-12-21Bibliographically approved
Thill, S., Riveiro, M., Lagerstedt, E., Lebram, M., Hemeren, P., Habibovic, A. & Klingegård, M. (2018). Driver adherence to recommendations from support systems improves if the systems explain why they are given: A simulator study. Transportation Research Part F: Traffic Psychology and Behaviour, 56, 420-435
Open this publication in new window or tab >>Driver adherence to recommendations from support systems improves if the systems explain why they are given: A simulator study
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2018 (English)In: Transportation Research Part F: Traffic Psychology and Behaviour, ISSN 1369-8478, E-ISSN 1873-5517, Vol. 56, p. 420-435Article in journal (Refereed) Published
Abstract [en]

This paper presents a large-scale simulator study on driver adherence to recommendationsgiven by driver support systems, specifically eco-driving support and navigation support.123 participants took part in this study, and drove a vehicle simulator through a pre-defined environment for a duration of approximately 10 min. Depending on the experi-mental condition, participants were either given no eco-driving recommendations, or asystem whose provided support was either basic (recommendations were given in theform of an icon displayed in a manner that simulates a heads-up display) or informative(the system additionally displayed a line of text justifying its recommendations). A naviga-tion system that likewise provided either basic or informative support, depending on thecondition, was also provided.

Effects are measured in terms of estimated simulated fuel savings as well as engine brak-ing/coasting behaviour and gear change efficiency. Results indicate improvements in allvariables. In particular, participants who had the support of an eco-driving system spenta significantly higher proportion of the time coasting. Participants also changed gears atlower engine RPM when using an eco-driving support system, and significantly more sowhen the system provided justifications. Overall, the results support the notion that pro-viding reasons why a support system puts forward a certain recommendation improvesadherence to it over mere presentation of the recommendation.

Finally, results indicate that participants’ driving style was less eco-friendly if the navi-gation system provided justifications but the eco-system did not. This may be due to par-ticipants considering the two systems as one whole rather than separate entities withindividual merits. This has implications for how to design and evaluate a given driver sup-port system since its effectiveness may depend on the performance of other systems in thevehicle.

Keywords
Driver behaviour, System awareness, Eco-friendly behaviour, Driver recommendation systems
National Category
Psychology Human Computer Interaction Information Systems
Research subject
Interaction Lab (ILAB); Skövde Artificial Intelligence Lab (SAIL); INF301 Data Science; INF302 Autonomous Intelligent Systems
Identifiers
urn:nbn:se:his:diva-15279 (URN)10.1016/j.trf.2018.05.009 (DOI)000437997700037 ()2-s2.0-85048505654 (Scopus ID)
Projects
TIEB
Funder
Swedish Energy Agency
Available from: 2018-06-04 Created: 2018-06-04 Last updated: 2019-11-19Bibliographically approved
Nair, V., Drejing, K. & Hemeren, P. (2018). Incidental processing of biological motion:: Effects of orientation, local-motion and global-form features. In: : . Paper presented at 41st European Conference on Visual Perception ECVP 2018, Trieste, Italy, August, 26–30, 2018 (pp. 35-36). ENGLAND: Sage Publications, 48
Open this publication in new window or tab >>Incidental processing of biological motion:: Effects of orientation, local-motion and global-form features
2018 (English)Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

Previous studies on biological motion perception indicate that the processing of biological motion is fast and automatic. A segment of these studies has shown that task irrelevant and to-be-ignored biological figures are incidentally processed since they interfere with the main task. However more evidence is needed to understand the role of local-motion and global-form processing mechanisms in incidentally processed biological figures. This study investigates the effects of local-motion and global-form features on incidental processing. Point light walkers (PLW) were used in a flanker paradigm in a direction discrimination task to assess the influence of the flankers. Our results show that upright oriented PLW flankers with global-form features have more influence on visual processing of the central PLW than inverted or scrambled PLW flankers with only local-motion features.

Place, publisher, year, edition, pages
ENGLAND: Sage Publications, 2018
Series
PERCEPTION, ISSN 0301-0066, E-ISSN 1468-4233
Keywords
Biological motion, perception, attention, action recognition
National Category
Applied Psychology
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-16522 (URN)000468288300131 ()
Conference
41st European Conference on Visual Perception ECVP 2018, Trieste, Italy, August, 26–30, 2018
Funder
Knowledge Foundation
Available from: 2018-12-21 Created: 2018-12-21 Last updated: 2019-06-07Bibliographically approved
Hemeren, P. (2018). Signals for Active Safety Systems to Detect Cyclists and Their Intentions in Traffic. In: : . Paper presented at The Eye, The Brain & The Auto - 8 th World Research Congress on Vision and Driving, Detroit, USA, October 7-9, 2018.
Open this publication in new window or tab >>Signals for Active Safety Systems to Detect Cyclists and Their Intentions in Traffic
2018 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Objectives: Human cognition is importantly predictive. This predictive ability can also be applied to predict the future actions of cyclists in traffic. Active safety systems in (semi-)autonomous vehicles will likely need to detect and predict human actions occurring in different traffic situations.

Results from two experiments demonstrate the effect of different patterns of human movement on predicting the behavior of the cyclists and the distance it takes drivers to detect the cyclists in a city environment. This research was carried out by observing recorded sequences on a computer but also in a driving simulator in order to include more naturalistic conditions and to achieve a high level of experimental control. As a complement to our previous research (Hemeren et al., 2014), we aimed to determine the distance at which drivers would detect and predict cyclists’ behavior.

Methods: Participants in both experiments (90 participants in experiment 1 and 24 in experiment 2) observed video-recorded cyclists wearing three different patterns of reflective clothing (Fig. 1): biomotion, vest and the legal minimum requirement (legal), in which no reflector material was worn by the cyclists. In experiment 1, participants were instructed to predict if an approaching cyclist would make a left-turn or continue straight on when approaching a crossing. This task was also performed during daylight, dusk and at night. In the second experiment, participants in a driving simulator indicated (as a secondary task) when they saw a cyclist riding along the side of the road.

Results: The biomotion reflective clothing led to a prediction accuracy of 88% for cyclists’ intentions at 9 meters before a crossing for the nighttime condition. For the legal minimum, the result was 59% and for the vest 67%. Detection distance in the driving simulator was also significantly greater for the biomotion condition compared to the legal and vest conditions. Visual detection is almost twice the distance for biomotion compared to the other two reflective clothing conditions.

Conclusions: The results point to the critical role that biological motion can play on predicting the intention and detection of cyclists in traffic. This information can be used to inform (semi-)autonomous systems of human intentions in traffic.

National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-16358 (URN)
Conference
The Eye, The Brain & The Auto - 8 th World Research Congress on Vision and Driving, Detroit, USA, October 7-9, 2018
Funder
Swedish Transport Administration, TRV 2015/85218
Available from: 2018-11-03 Created: 2018-11-03 Last updated: 2019-05-23Bibliographically approved
Hemeren, P., Hanley, E. & Veto, P. (2018). The walker congruency effect and incidental processing of configural and local features in point-light walkers. In: : . Paper presented at 41st European Conference on Visual Perception ECVP 2018, 26-30 August, Trieste Italy. (pp. 36-36). England: Sage Publications, 48
Open this publication in new window or tab >>The walker congruency effect and incidental processing of configural and local features in point-light walkers
2018 (English)Conference paper, Poster (with or without abstract) (Other academic)
Abstract [en]

Two visual flanker experiments investigated the roles of configural and local opponent motion cues on the incidental processing of a point-light walker with diagonally configured limbs. Different flankers were used to determine the extent of interference on the visual processing of a central walker. Flankers (walkers) with diagonally configured limbs lacked the local opponent motion of the feet and hands, but contained configural information. Partially scrambled displays with intact opponent motion of the feet at the bottom of the display lacked configural information. These two conditions resulted in different effects of incidental processing. Configural information, without opponent motion, leads to changes in reaction time across flanker conditions, with no measurable congruency effect, while feet-based opponent motion causes a congruency effect without changes in reaction time across different flanker conditions. Life detection is a function of both sources of information.

Place, publisher, year, edition, pages
England: Sage Publications, 2018
Series
PERCEPTION, ISSN 0301-0066, E-ISSN 1468-4233
Keywords
biological motion, intention recognition, attention, social cognition
National Category
Interaction Technologies
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-16355 (URN)000468288300133 ()
Conference
41st European Conference on Visual Perception ECVP 2018, 26-30 August, Trieste Italy.
Funder
Knowledge Foundation, 20140220
Available from: 2018-11-03 Created: 2018-11-03 Last updated: 2019-06-07Bibliographically approved
Sun, J., Billing, E., Seoane, F., Zhou, B., Högberg, D. & Hemeren, P. (2017). Categories of touch: Classifying human touch using a soft tactile sensor. In: : . Paper presented at The robotic sense of touch: From sensing to understanding, workshop at the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 29, 2017.
Open this publication in new window or tab >>Categories of touch: Classifying human touch using a soft tactile sensor
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2017 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

Social touch plays an important role not only in human communication but also in human-robot interaction. We here report results from an ongoing study on affective human-robot interaction. In our previous research, touch type is shown to be informative for communicated emotion. Here, a soft matrix array sensor is used to capture the tactile interaction between human and robot and a method based on PCA and kNN is applied in the experiment to classify different touch types, constituting a pre-stage to recognizing emotional tactile interaction. Results show an average recognition rate for classified touch type of 71%, with a large variability between different types of touch. Results are discussed in relation to affective HRI and social robotics.

National Category
Signal Processing
Research subject
Interaction Lab (ILAB); User Centred Product Design; INF202 Virtual Ergonomics; INF302 Autonomous Intelligent Systems
Identifiers
urn:nbn:se:his:diva-13838 (URN)
Conference
The robotic sense of touch: From sensing to understanding, workshop at the IEEE International Conference on Robotics and Automation (ICRA), Singapore, May 29, 2017
Projects
Design, Textiles, and Sustainable Development
Funder
Region Västra Götaland
Available from: 2017-06-22 Created: 2017-06-22 Last updated: 2019-03-04Bibliographically approved
Hemeren, P. E., Johannesson, M., Lebram, M. & Eriksson, F. (2017). Detecting Cyclists at Night: visibility effects of reflector placement and different lighting conditions. In: Proceedings of the 6th Annual International Cycling Safety Conference: . Paper presented at 6th Annual International Cycling Safety Conference. Davis, California, USA, September 21-22, 2017.
Open this publication in new window or tab >>Detecting Cyclists at Night: visibility effects of reflector placement and different lighting conditions
2017 (English)In: Proceedings of the 6th Annual International Cycling Safety Conference, 2017Conference paper, Oral presentation with published abstract (Refereed)
Keywords
biological motion, cyclist visibility, reflectors, attention, night driving
National Category
Applied Psychology
Research subject
Interaction Lab (ILAB)
Identifiers
urn:nbn:se:his:diva-14706 (URN)
Conference
6th Annual International Cycling Safety Conference. Davis, California, USA, September 21-22, 2017
Available from: 2018-02-01 Created: 2018-02-01 Last updated: 2018-03-26Bibliographically approved
Sun, J., Redyuk, S., Billing, E., Högberg, D. & Hemeren, P. (2017). Tactile Interaction and Social Touch: Classifying Human Touch using a Soft Tactile Sensor. In: HAI '17: Proceedings of the 5th International Conference on Human Agent Interaction. Paper presented at 5th International Conference on Human-Agent Interaction, Bielefeld, Germany, 17-20 October 2017 (pp. 523-526). New York: Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Tactile Interaction and Social Touch: Classifying Human Touch using a Soft Tactile Sensor
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2017 (English)In: HAI '17: Proceedings of the 5th International Conference on Human Agent Interaction, New York: Association for Computing Machinery (ACM), 2017, p. 523-526Conference paper, Poster (with or without abstract) (Refereed)
Abstract [en]

This paper presents an ongoing study on affective human-robot interaction. In our previous research, touch type is shown to be informative for communicated emotion. Here, a soft matrix array sensor is used to capture the tactile interaction between human and robot and 6 machine learning methods including CNN, RNN and C3D are implemented to classify different touch types, constituting a pre-stage to recognizing emotional tactile interaction. Results show an average recognition rate of 95% by C3D for classified touch types, which provide stable classification results for developing social touch technology. 

Place, publisher, year, edition, pages
New York: Association for Computing Machinery (ACM), 2017
Keywords
Tactile interaction, social touch, affective HRI, machine learning
National Category
Computer Vision and Robotics (Autonomous Systems)
Research subject
Interaction Lab (ILAB); User Centred Product Design; INF202 Virtual Ergonomics; INF302 Autonomous Intelligent Systems
Identifiers
urn:nbn:se:his:diva-14282 (URN)10.1145/3125739.3132614 (DOI)463009800078 ()2-s2.0-85034856772 (Scopus ID)978-1-4503-5113-3 (ISBN)
Conference
5th International Conference on Human-Agent Interaction, Bielefeld, Germany, 17-20 October 2017
Projects
Design, textil och hållbar utveckling (VGR)
Funder
Region Västra Götaland
Available from: 2017-10-31 Created: 2017-10-31 Last updated: 2019-09-09Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-1227-6843

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