| 1. |
- Kondyli, Vasiliki, 1989-
(författare)
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Behavioural Principles for the Design of Human-Centred Cognitive Technologies : The Case of Visuo-Locomotive Experience
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The successful application, usability, and social emancipation of AI technologies necessitates that the design and implementation of technical systems be founded on human-centred principles, be it cognitive or behavioural, social, ethical etc. Towards this objective, this thesis develops an interdisciplinary methodology for embedding cognitive behavioural principles in the design and development of next-generation human-centred AI technologies that aim to assist and empower humans in everyday life.The interdisciplinary methodology developed in this research categorically focusses on two key aspects pertaining to human-centred technology design and engineering: (1) human behavioural precedents; and (2) cognitively founded representational and computational modalities:Human behavioural precedents are established by systematically analysing human visuo-locomotive experience during everyday activities involving (embodied) multimodal interactions. We conduct naturalistic behavioural experiments focusing on aspects of visual perception (e.g., inattention blindness) and spatial cognition (e.g., orientation, navigation) in diverse settings of everyday mobility. As specific -in-the-wild- experimental contexts, we focus on behavioural aspects involved in everyday (human) navigation and driving.Representational and computational modalities are developed based on cognitively-driven articulation of behavioural precedents. Particularly, a cognitive model of visuospatial complexity for grounding embodied multimodal interactions is developed by incorporating behavioural precedents pertaining to representations of space, motion, and interaction. Furthermore, precedents concerning human preferences are used as a basis for semantically-driven computational synthesis (e.g. in the generation and manipulation of spatial morphologies), and in the articulation of human-centred evaluation and standardisation of AI systems.As case studies we demonstrate the developed methodology in the backdrop of two application domains: (a) design assistance technologies, and (b) autonomous driving. More broadly, this thesis emphasises the need for embedding ecologically valid behavioural knowledge within the development of "human-centred" technologies. Furthermore, this research paves the way for the development of systems that understand, interpret and anticipate human behaviour under ecologically valid naturalistic circumstances.
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| 2. |
- Sioutis, M., et al.
(författare)
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Preface
- 2023
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Ingår i: CEUR Workshop Proceedings. - : Technical University of Aachen. - 1613-0073. ; 3475
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)
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| 3. |
- Barreiro, Anabela, et al.
(författare)
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Multi3Generation : Multitask, Multilingual, Multimodal Language Generation
- 2022
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Ingår i: Proceedings of the 23rd Annual Conference of the European Association for Machine Translation. - : European Association for Machine Translation. ; , s. 345-346
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Konferensbidrag (refereegranskat)abstract
- This paper presents the Multitask, Multilingual, Multimodal Language Generation COST Action – Multi3Generatio(CA18231), an interdisciplinary networof research groups working on different aspects of language generation. This "meta-paper" will serve as reference for citationof the Action in future publications. It presents the objectives, challenges and a the links for the achieved outcomes.
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| 4. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Artificial Visual Intelligence : Perceptual Commonsense for Human-Centred Cognitive Technologies
- 2023
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Ingår i: Human-Centered Artificial Intelligence. - : Springer. - 9783031243486 - 9783031243493 ; , s. 216-242
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Bokkapitel (refereegranskat)abstract
- 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.
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| 5. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Cognitive Vision and Perception : Deep Semantics Integrating AI and Vision for Reasoning about Space, Motion, and Interaction
- 2020
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Ingår i: ECAI 2020. - : IOS Press. - 9781643681009 - 9781643681016 ; , s. 2881-2882
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Konferensbidrag (refereegranskat)abstract
- Semantic interpretation of dynamic visuospatial imagery calls for a general and systematic integration of methods in knowledge representation and computer vision. Towards this, we highlight research articulating & developing deep semantics, characterised by the existence of declarative models –e.g., pertaining space and motion– and corresponding formalisation and reasoning methods sup- porting capabilities such as semantic question-answering, relational visuospatial learning, and (non-monotonic) visuospatial explanation. We position a working model for deep semantics by highlighting select recent / closely related works from IJCAI, AAAI, ILP, and ACS. We posit that human-centred, explainable visual sensemaking necessitates both high-level semantics and low-level visual computing, with the highlighted works providing a model for systematic, modular integration of diverse multifaceted techniques developed in AI, ML, and Computer Vision.
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| 6. |
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| 7. |
- Kondyli, Vasiliki, 1989-, et al.
(författare)
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A Cognitive Model of Visuospatial Complexity for Interactive Immersive Media Design
- 2022
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 8. |
- Kondyli, Vasiliki, 1989-, et al.
(författare)
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Analysing Driver (In)Attentiveness : Towards a Cognitive Complexity Model Combining Visuospatial and Interactional Parameters
- 2022
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 9. |
- Kondyli, Vasiliki, 1989-, et al.
(författare)
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Cognitive Modelling of Visuospatial Complexity in the Streetscape
- 2021
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Ingår i: Proceedings of the 8th International Conference on Spatial Cognition: Cognition and Action in a Plurality of Spaces (ICSC 2021). - : Springer. ; , s. 44-44
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Konferensbidrag (refereegranskat)abstract
- Background: Incorporating knowledge about human behaviour and the effect of the environment is a major goal for the design and engineering of human-centred autonomous vehicles. Systems that aim to establish a common interaction ground with humans require systematic modelling of empirically established behavioural norms customised to specific contexts.Aims: Focusing on aspects pertaining to visual attention in driving, we develop a cognitive model of visuospatial complexity for naturalistic driving scenes and explore its effect on visual attention tasks (e.g., involving visual search) during everyday driving.Methods: By analyzing dynamic naturalistic scenes, we define a scale of visuospatial complexity based on a taxonomy of quantitative, structural, and dynamic attributes. We re-create real-world instances in virtual reality (VR) in four levels of visuospatial complexity. The human-centred basis of the model lies in its behavioural evaluation with human subjects with respect to psychophysical measures (e.g. eye-tracking) pertaining to embodied visuospatial attention.Results: Empirical results show the levels of visuospatial complexity of the scene correlate with visual search performance parameters, however different categories of attributes contribute differently to the overall effect. We report work-in-progress on the development of a (sample) dataset with the central emphasis on the evaluation of the visuospatial complexity levels on driving stimuli within VR.Conclusion: The presented cognitive model of visuospatial complexity in everyday driving situations can be used as a basis to design, and evaluate visuospatial sensemaking capabilities of autonomous vehicles. We posit that our methodology encapsulates key cognitive principles founded on empirically established behavioural patterns under naturalistic conditions.
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| 10. |
- Kondyli, Vasiliki, 1989-, et al.
(författare)
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Drivers avoid attentional elaboration under safety-critical situations and complex environments
- 2023
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Ingår i: 17th European Workshop on Imagery and Cognition. ; , s. 18-18
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Konferensbidrag (refereegranskat)abstract
- 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.
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