To Örebro University

oru.seÖrebro University Publications
Change search
Link to record
Permanent link

Direct link
Bhatt, Mehul, ProfessorORCID iD iconorcid.org/0000-0002-6290-5492
Biography [eng]

 

 
Biography [swe]

 

 
Publications (10 of 128) Show all publications
Bhatt, M. & Suchan, J. (2023). Artificial Visual Intelligence: Perceptual Commonsense for Human-Centred Cognitive Technologies. In: Chetouani, Mohamed; Dignum, Virginia; Lukowicz, Paul; Sierra, Carles (Ed.), Human-Centered Artificial Intelligence: Advanced Lectures (pp. 216-242). Springer
Open this publication in new window or tab >>Artificial Visual Intelligence: Perceptual Commonsense for Human-Centred Cognitive Technologies
2023 (English)In: Human-Centered Artificial Intelligence: Advanced Lectures / [ed] Chetouani, Mohamed; Dignum, Virginia; Lukowicz, Paul; Sierra, Carles, Springer, 2023, p. 216-242Chapter in book (Refereed)
Abstract [en]

We address computational cognitive vision and perception at the interface of language, logic, cognition, and artificial intelligence. The chapter presents general methods for the processing and semantic interpretation of dynamic visuospatial imagery with a particular emphasis on the ability to abstract, learn, and reason with cognitively rooted structured characterisations of commonsense knowledge pertaining to space and motion. The presented work constitutes a systematic model and methodology integrating diverse, multi-faceted AI methods pertaining Knowledge Representation and Reasoning, Computer Vision, and Machine Learning towards realising practical, human-centred artificial visual intelligence.

Place, publisher, year, edition, pages
Springer, 2023
Series
Lecture Notes in Computer Science (LNCS), ISSN 0302-9743, E-ISSN 1611-3349 ; 13500
Keywords
Cognitive vision, Knowledge representation and reasoning, Commonsense reasoning, Deep semantics, Declarative spatial reasoning, Computer vision, Computational models of narrative, Human-centred computing and design, Spatial cognition and AI, Visual perception, Multimodal interaction, Autonomous driving, HRI, Media, Visual art
National Category
Computer Sciences Human Computer Interaction Psychology
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-105389 (URN)10.1007/978-3-031-24349-3_12 (DOI)9783031243486 (ISBN)9783031243493 (ISBN)
Funder
Swedish Research Council
Available from: 2023-04-06 Created: 2023-04-06 Last updated: 2023-04-11Bibliographically approved
Kondyli, V., Daniel, L. & Bhatt, M. (2023). Drivers avoid attentional elaboration under safety-critical situations and complex environments. In: 17th European Workshop on Imagery and Cognition: . Paper presented at 17th European Workshop on Imagery and Cognition, Anglia Ruskin University, Cambridge, UK, June 20-22, 2023 (pp. 18-18).
Open this publication in new window or tab >>Drivers avoid attentional elaboration under safety-critical situations and complex environments
2023 (English)In: 17th European Workshop on Imagery and Cognition, 2023, p. 18-18Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

In everyday activities where continuous visual awareness is critical such as driving, several cognitive processes pertaining to visual attention are of the essence, for instance, change detection, anticipation, monitoring, etc. Research suggests that environmental load and task difficulty contribute to failures in visual perception that can be essential for detecting and reacting to safety-critical incidents. However, it is unclear how gaze patterns and attentional strategies are compromised because of environmental complexity in naturalistic driving. In a change detection task during everyday simulated driving, we investigate inattention blindness in relation to environmental complexity and the kind of interaction incidents drivers address. We systematically analyse and evaluate safety-critical situations from real-world driving videos and replicate a number of them in a virtual driving experience. Participants (N= 80) aged 23-45 years old, drove along three levels of environmental complexity (low-medium-high) and various incidents of interaction with roadside users (e.g., pedestrians, cyclists, pedestrians in a wheelchair), categorized as safety critical or not. Participants detected changes in the behaviour of road users and in object properties. We collect multimodal data including eye-tracking, egocentric view videos, movement trace, head movements, driving behaviour, and detection button presses. Results suggest that gaze behaviour (number and duration of fixations, 1st fixation on AOI) is affected negatively by an increase in environmental complexity, but the effect is moderate for safety-critical incidents. Moreover, anticipatory and monitoring attention was crucial for detecting critical changes in behaviour and reacting on time. However, in highly complex environments participants effectively limit attentional monitoring and lingering for non-critical changes and they also controlled “look-but-fail-to-see errors", especially while addressing a safety-related event. We conclude that drivers change attentional strategies, avoiding non-productive forms of attentional elaboration (anticipatory and monitoring) and efficiently disengaging from targets when the task difficulty is high. We discuss the implications for driving education and research driven development of autonomous driving. 

Keywords
Visual perception, Change blindness, Visuospatial complexity, Attentional strategies, Naturalistic observation, Everyday driving
National Category
Psychology Computer Sciences Transport Systems and Logistics
Research subject
Psychology; Computer Science
Identifiers
urn:nbn:se:oru:diva-108117 (URN)
Conference
17th European Workshop on Imagery and Cognition, Anglia Ruskin University, Cambridge, UK, June 20-22, 2023
Projects
Counterfactual Commonsense
Funder
Örebro UniversityEU, Horizon 2020, 754285Swedish Research Council
Available from: 2023-09-06 Created: 2023-09-06 Last updated: 2023-09-07Bibliographically approved
Kondyli, V., Bhatt, M., Levin, D. & Suchan, J. (2023). How do drivers mitigate the effects of naturalistic visual complexity? On attentional strategies and their implications under a change blindness protocol. Cognitive Research: Principles and Implications, 8(1), Article ID 54.
Open this publication in new window or tab >>How do drivers mitigate the effects of naturalistic visual complexity? On attentional strategies and their implications under a change blindness protocol
2023 (English)In: Cognitive Research: Principles and Implications, E-ISSN 2365-7464, Vol. 8, no 1, article id 54Article in journal (Refereed) Published
Abstract [en]

How do the limits of high-level visual processing affect human performance in naturalistic, dynamic settings of (multimodal) interaction where observers can draw on experience to strategically adapt attention to familiar forms of complexity? In this backdrop, we investigate change detection in a driving context to study attentional allocation aimed at overcoming environmental complexity and temporal load. Results indicate that visuospatial complexity substantially increases change blindness but also that participants effectively respond to this load by increasing their focus on safety-relevant events, by adjusting their driving, and by avoiding non-productive forms of attentional elaboration, thereby also controlling “looked-but-failed-to-see” errors. Furthermore, analyses of gaze patterns reveal that drivers occasionally, but effectively, limit attentional monitoring and lingering for irrelevant changes. Overall, the experimental outcomes reveal how drivers exhibit effective attentional compensation in highly complex situations. Our findings uncover implications for driving education and development of driving skill-testing methods, as well as for human-factors guided development of AI-based driving assistance systems.

Place, publisher, year, edition, pages
Springer, 2023
Keywords
Visual perception, Change blindness, Visuospatial complexity, Attentional strategies, Naturalistic observation, Everyday driving
National Category
Psychology Computer Sciences Transport Systems and Logistics
Research subject
Psychology; Computer Science
Identifiers
urn:nbn:se:oru:diva-107517 (URN)10.1186/s41235-023-00501-1 (DOI)001044388200001 ()37556047 (PubMedID)2-s2.0-85167370133 (Scopus ID)
Projects
Counterfactual Commonsense
Funder
Örebro UniversitySwedish Research CouncilEU, Horizon 2020, 754285
Available from: 2023-08-10 Created: 2023-08-10 Last updated: 2023-09-27Bibliographically approved
Nair, V., Hemeren, P., Vignolo, A., Noceti, N., Nicora, E., Sciutti, A., . . . Sandini, G. (2023). Kinematic primitives in action similarity judgments: A human-centered computational model. IEEE Transactions on Cognitive and Developmental Systems, 15(4), 1981-1992
Open this publication in new window or tab >>Kinematic primitives in action similarity judgments: A human-centered computational model
Show others...
2023 (English)In: IEEE Transactions on Cognitive and Developmental Systems, ISSN 2379-8920, Vol. 15, no 4, p. 1981-1992Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
IEEE, 2023
Keywords
Action similarity, action matching, biological motion, optical flow, point light display, kinematic primitives, computational model, comparative study
National Category
Psychology Computer Sciences Human Computer Interaction Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-103866 (URN)10.1109/TCDS.2023.3240302 (DOI)2-s2.0-85148457281 (Scopus ID)
Funder
Knowledge Foundation, 2014022EU, Horizon 2020, 804388
Note

Funding agency:

AFOSR FA8655-20-1-7035

Available from: 2023-01-31 Created: 2023-01-31 Last updated: 2024-02-05Bibliographically approved
Lloret, E., Barreiro, A., Bhatt, M., Bugarín-Diz, A., Modoni, G. E., Silberztein, M., . . . Erdem, A. (2023). Multi3Generation: Multitask, Multilingual, and Multimodal Language Generation. Open Research Europe, 3, Article ID 176.
Open this publication in new window or tab >>Multi3Generation: Multitask, Multilingual, and Multimodal Language Generation
Show others...
2023 (English)In: Open Research Europe, E-ISSN 2732-5121, Vol. 3, article id 176Article in journal (Refereed) Published
Abstract [en]

The purpose of this article is to highlight the critical importance of language generation today. In particular, language generation is explored from the following three aspects: multi-modality, multilinguality, and multitask, which all of them play crucial role for Natural Language Generation (NLG) community. We present the activities conducted within the Multi3Generation COST Action (CA18231), as well as current trends and future perspectives for multitask, multilingual and multimodal language generation.

Place, publisher, year, edition, pages
European Commission, 2023
Keywords
Language Technologies, Multi-task, Multi3Generation, Multilinguality, Multimodality, Natural Language Generation
National Category
Language Technology (Computational Linguistics)
Identifiers
urn:nbn:se:oru:diva-110610 (URN)10.12688/openreseurope.16307.1 (DOI)38131050 (PubMedID)2-s2.0-85180942557 (Scopus ID)
Funder
Örebro UniversitySwedish Research Council
Note

This project has received funding from the European Cooperation in Science and Technology (COST) under the agreement no. CA18231 - Multi3Generation: Multitask, Multilingual, Multimodal Language Generation. In addition, this research work is partially conducted within the R&D projects “CORTEX: Conscious Text Generation” (PID2021-123956OB-I00) partially funded by MCIN/ AEI/10.13039/501100011033/ and by “ERDF A way of making Europe” and “Enhancing the modernization public sector organizations by deploying Natural Language Processing to make their digital content CLEARER to those with cognitive disabilities” (TED2021-130707B-I00), funded by MCIN/AEI/10.13039/501100011033 and “European Union NextGenerationEU/PRTR”, and by the Generalitat Valenciana through the project “NL4DISMIS: Natural Language Technologies for dealing with dis- and misinformation with grant reference (CIPROM/2021/21)”, Project Counterfactual Commonsense (Örebro University), funded by the Swedish Research Council (VR).

Available from: 2024-01-09 Created: 2024-01-09 Last updated: 2024-01-09Bibliographically approved
Sioutis, M., Long, Z., Lee, J., Bhatt, M., Toumpa, A., Finzel, B., . . . Bouraoui, Z. (2023). Preface. Paper presented at 2nd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2023), Macao, China, August 21, 2023. CEUR Workshop Proceedings, 3475
Open this publication in new window or tab >>Preface
Show others...
2023 (English)In: CEUR Workshop Proceedings, E-ISSN 1613-0073, Vol. 3475Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
Technical University of Aachen, 2023
National Category
Computer Sciences
Identifiers
urn:nbn:se:oru:diva-110217 (URN)2-s2.0-85173489517 (Scopus ID)
Conference
2nd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2023), Macao, China, August 21, 2023
Available from: 2023-12-14 Created: 2023-12-14 Last updated: 2023-12-14Bibliographically approved
Sioutis, M., Long, Z., Lee, J. H. & Bhatt, M. (Eds.). (2023). Proceedings of the 2nd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2023) co-located with the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), Macao, S.A.R., August 21, 2023. Paper presented at 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), Macao, S.A.R., August 21, 2023. Technical University of Aachen, 3475
Open this publication in new window or tab >>Proceedings of the 2nd International Workshop on Spatio-Temporal Reasoning and Learning (STRL 2023) co-located with the 32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), Macao, S.A.R., August 21, 2023
2023 (English)Conference proceedings (editor) (Refereed)
Place, publisher, year, edition, pages
Technical University of Aachen, 2023
Series
CEUR Workshop Proceedings, E-ISSN 1613-0073 ; 3475
Keywords
Artificial Intelligence, Declarative Spatial Reasoning, Neurosymbolic AI
National Category
Computer Sciences
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-108114 (URN)
Conference
32nd International Joint Conference on Artificial Intelligence (IJCAI 2023), Macao, S.A.R., August 21, 2023
Available from: 2023-09-06 Created: 2023-09-06 Last updated: 2024-01-16Bibliographically approved
Suchan, J., Bhatt, M. & Varadarajan, S. (2023). Visual Sensemaking Needs Both Vision and Semantics: On Logic-Based Declarative Neurosymbolism for Reasoning about Space and Motion. In: Enrico Pontelli; Stefania Costantini; Carmine Dodaro; Sarah Gaggl; Roberta Calegari; Artur D'Avila Garcez; Francesco Fabiano; Alessandra Mileo; Alessandra Russo; Francesca Toni (Ed.), Proceedings: 39th International Conference on Logic Programming, Imperial College London, UK, 9th July 2023 - 15th July 2023. Paper presented at 39th International Conference on Logic Programming (ICLP 2023), London, United Kingdom, July 9-15, 2023 (pp. 393-395). Open Publishing Association, 385
Open this publication in new window or tab >>Visual Sensemaking Needs Both Vision and Semantics: On Logic-Based Declarative Neurosymbolism for Reasoning about Space and Motion
2023 (English)In: Proceedings: 39th International Conference on Logic Programming, Imperial College London, UK, 9th July 2023 - 15th July 2023 / [ed] Enrico Pontelli; Stefania Costantini; Carmine Dodaro; Sarah Gaggl; Roberta Calegari; Artur D'Avila Garcez; Francesco Fabiano; Alessandra Mileo; Alessandra Russo; Francesca Toni, Open Publishing Association , 2023, Vol. 385, p. 393-395Conference paper, Published paper (Refereed)
Place, publisher, year, edition, pages
Open Publishing Association, 2023
Series
Electronic Proceedings in Theoretical Computer Science (EPTCS), E-ISSN 2075-2180 ; 385
Keywords
Artificial Intelligence, Cognitive Vision, Semantics, Narrative, Visual Intelligence, Visual Sensemaking, Commonsense Reasoning
National Category
Computer Sciences Computer Vision and Robotics (Autonomous Systems)
Research subject
Computer Science
Identifiers
urn:nbn:se:oru:diva-107982 (URN)10.4204/EPTCS.385 (DOI)
Conference
39th International Conference on Logic Programming (ICLP 2023), London, United Kingdom, July 9-15, 2023
Projects
Counterfactual Commonsense
Funder
Swedish Research Council, p2558
Available from: 2023-08-31 Created: 2023-08-31 Last updated: 2024-01-16Bibliographically approved
Kondyli, V., Bhatt, M. & Suchan, J. (2022). A Cognitive Model of Visuospatial Complexity for Interactive Immersive Media Design. In: : . Paper presented at Society for the Cognitive Studies of the Moving Image Conference (SCSMI 2022), Gandia, Spain, June 1-4, 2022.
Open this publication in new window or tab >>A Cognitive Model of Visuospatial Complexity for Interactive Immersive Media Design
2022 (English)Conference paper, Oral presentation with published abstract (Refereed)
Abstract [en]

The development of immersive visuoauditory media brings to the fore several design challenges concerning cognitive human factors, such as visual perception, embodied interaction, and emotional engagement. With a focus on visual perception, our research emphasises a systematic study of embodied multimodal interaction in immersive settings and provides a cognitive model of visuospatial complexity through a series of behavioural studies in VR with human subjects. We report preliminary results on the effect of levels of visuospatial complexity on visuospatial attention patterns and visual search performance. The proposed methodology provides a general foundation for conducting naturalistic studies in immersive perception and interaction, e.g., in the context of established paradigms such as event perception, ensemble perception, visual search and foraging, change blindness. Moreover, we posit that the demonstrated confluence of computational and behavioural studies is needed to better appreciate the complexity and spectrum of varied human-centred challenges in the design of immersive media.

Keywords
Embodied Interaction, Visual Perception, Naturalistic Studies, Immersive Media, Multimodality
National Category
Computer and Information Sciences Psychology (excluding Applied Psychology) Human Computer Interaction
Research subject
Computer Science; Psychology
Identifiers
urn:nbn:se:oru:diva-98857 (URN)
Conference
Society for the Cognitive Studies of the Moving Image Conference (SCSMI 2022), Gandia, Spain, June 1-4, 2022
Note

The ISBN no and other publication info will be published after the conference, June 1-4.

Available from: 2022-05-05 Created: 2022-05-05 Last updated: 2022-06-10Bibliographically approved
Kondyli, V. & Bhatt, M. (2022). Analysing Driver (In)Attentiveness: Towards a Cognitive Complexity Model Combining Visuospatial and Interactional Parameters. In: : . Paper presented at 8th International Conference on Driver Distraction and Inattention (DDI 2022), Gothenburg, Sweden, October 19-20, 2022.
Open this publication in new window or tab >>Analysing Driver (In)Attentiveness: Towards a Cognitive Complexity Model Combining Visuospatial and Interactional Parameters
2022 (English)Conference paper, Published paper (Refereed)
Abstract [en]

We investigate the role of visuospatial environmental cues on driver (in)attention in everyday naturalistic driving situations. We develop a cognitive model of visuospatial complexity incorporating two critical aspects influencing visual (in)attention: (1) multimodal interaction mechanisms such as gesture, joint attention amongst roadside stakeholders (e.g. pedestrians, cyclists, drivers); and (2) visuospatial environmental features such as clutter, motion, environmental structure. 

Our research emphasises the manner in which a cognitive human-factors guided model to analyse attentiveness can be applied to systematically explore the effects of a combination of environmental and interactional characteristics on visual attention in naturalistic driving. We position the application of the developed cognitive model to serve a foundational purpose in the training and testing of novel driver assistance technologies, e.g., from the viewpoint of systematic compliance with human-centered design guidelines.

Keywords
visual attention, multimodality, naturalistic studies, embodied interactions, driving, cognitive technologies
National Category
Psychology Computer and Information Sciences
Research subject
Computer Science; Physiology
Identifiers
urn:nbn:se:oru:diva-100521 (URN)
Conference
8th International Conference on Driver Distraction and Inattention (DDI 2022), Gothenburg, Sweden, October 19-20, 2022
Available from: 2022-08-09 Created: 2022-08-09 Last updated: 2022-10-28Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-6290-5492

Search in DiVA

Show all publications