| 1. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Artificial Intelligence for Predictive and Evidence Based Architecture Design
- 2016
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Ingår i: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16). - : AAAI press. - 9781577357605 ; , s. 4349-4350
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Konferensbidrag (refereegranskat)abstract
- The evidence-based analysis of people's navigation and wayfinding behaviour in large-scale built-up environments (e.g., hospitals, airports) encompasses the measurement and qualitative analysis of a range of aspects including people's visual perception in new and familiar surroundings, their decision-making procedures and intentions, the affordances of the environment itself, etc. In our research on large-scale evidence-based qualitative analysis of wayfinding behaviour, we construe visual perception and navigation in built-up environments as a dynamic narrative construction process of movement and exploration driven by situation-dependent goals, guided by visual aids such as signage and landmarks, and influenced by environmental (e.g., presence of other people, time of day, lighting) and personal (e.g., age, physical attributes) factors. We employ a range of sensors for measuring the embodied visuo-locomotive experience of building users: eye-tracking, egocentric gaze analysis, external camera based visual analysis to interpret fine-grained behaviour (e.g., stopping, looking around, interacting with other people), and also manual observations made by human experimenters. Observations are processed, analysed, and integrated in a holistic model of the visuo-locomotive narrative experience at the individual and group level. Our model also combines embodied visual perception analysis with analysis of the structure and layout of the environment (e.g., topology, routes, isovists) computed from available 3D models of the building. In this framework, abstract regions like the visibility space, regions of attention, eye movement clusters, are treated as first class visuo-spatial and iconic objects that can be used for interpreting the visual experience of subjects in a high-level qualitative manner. The final integrated analysis of the wayfinding experience is such that it can even be presented in a virtual reality environment thereby providing an immersive experience (e.g., using tools such as the Oculus Rift) of the qualitative analysis for single participants, as well as for a combined analysis of large group. This capability is especially important for experiments in post-occupancy analysis of building performance. Our construction of indoor wayfinding experience as a form of moving image analysis centralizes the role and influence of perceptual visuo-spatial characteristics and morphological features of the built environment into the discourse on wayfinding research. We will demonstrate the impact of this work with several case-studies, particularly focussing on a large-scale experiment conducted at the New Parkland Hospital in Dallas Texas, USA.
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| 2. |
- 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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| 3. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Cognitive Interpretation of Everyday Activities - Toward Perceptual Narrative Based Visuo-Spatial Scene Interpretation
- 2013
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Ingår i: 2013 Workshop on Computational Models of Narrative. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik. - 9783939897576 ; , s. 24-29
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Konferensbidrag (refereegranskat)abstract
- We position a narrative-centred computational model for high-level knowledge representation and reasoning in the context of a range of assistive technologies concerned with visuo-spatial perception and cognition tasks. Our proposed narrative model encompasses aspects such as space, events, actions, change, and interaction from the viewpoint of commonsense reasoning and learning in large-scale cognitive systems. The broad focus of this paper is on the domain of human-activity interpretation in smart environments, ambient intelligence etc. In the backdrop of a smart meeting cinematography domain, we position the proposed narrative model, preliminary work on perceptual narrativisation, and the immediate outlook on constructing general-purpose open-source tools for perceptual narrativisation.
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| 4. |
- 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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| 5. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Declarative Spatial Reasoning for Intelligent Cinematography
- 2017
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Ingår i: Workshop on Intelligent Cinematography and Editing, WICED 2017. - : Eurographics Association. - 9783038680314
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Konferensbidrag (refereegranskat)abstract
- We present computational visuo-spatial representation and reasoning from the viewpoint of the research areas of artificial intelligence, spatial cognition and computation, and human-computer interaction. The particular focus is on demonstrating recent advances in the theory and practice of spatial reasoning, and its significance and potential as a foundational AI method for (intelligent) computational cinematography & editing systems.
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| 6. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Deep Semantics for Explainable Visuospatial Intelligence : Perspectives on Integrating Commonsense Spatial Abstractions and Low-Level Neural Features
- 2019
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Ingår i: Proceedings of the 2019 International Workshop on Neural-Symbolic Learning and Reasoning.
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Konferensbidrag (refereegranskat)abstract
- High-level semantic interpretation of (dynamic) visual imagery calls for general and systematic methods integrating techniques in knowledge representation and computer vision. Towards this, we position "deep semantics", denoting the existence of declarative models –e.g., pertaining "space and motion"– and corresponding formalisation and methods supporting (domain-independent) explainability capabilities such as semantic question-answering, relational (and relationally-driven) visuospatial learning, and (non-monotonic) visuospatial abduction. Rooted in recent work, we summarise and report the status quo on deep visuospatial semantics —and our approach to neurosymbolic integration and explainable visuo-spatial computing in that context— with developed methods and tools in diverse settings such as behavioural research in psychology, art & social sciences, and autonomous driving.
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| 7. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Embodied visuo-locomotive experience analysis : immersive reality based summarisation of experiments in environment-behaviour studies
- 2016
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Ingår i: Proceedings of the ACM Symposium on Applied Perception (SAP 2016). - USA : ACM Digital Library. - 9781450343831 ; , s. 133-133
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Konferensbidrag (refereegranskat)abstract
- Evidence-based design (EBD) for architecture involves the study of post-occupancy behaviour of building users with the aim to provide an empirical basis for improving building performance [Hamilton and Watkins 2009]. Within EBD, the high-level, qualitative analysis of the embodied visuo-locomotive experience of representative groups of building users (e.g., children, senior citizens, individuals facing physical challenges) constitutes a foundational approach for understanding the impact of architectural design decisions, and functional building performance from the viewpoint of areas such as environmental psychology, wayfinding research, human visual perception studies, spatial cognition, and the built environment [Bhatt and Schultz 2016].
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| 8. |
- Bhatt, Mehul, Professor, 1980-, et al.
(författare)
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Rotunde - A Smart Meeting Cinematography Initiative : Tools, Datasets, and Benchmarks for Cognitive Interpretation and Control
- 2013
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Ingår i: Space, Time, and Ambient Intelligence, Papers from the 2013 AAAI Workshop, Bellevue, Washington, USA, July 14, 2013. - : AI Access Foundation. - 9781577356257 ; , s. 9-12
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Konferensbidrag (refereegranskat)
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| 9. |
- 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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| 10. |
- Kondyli, Vasiliki, 1989-, et al.
(författare)
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Grounding Embodied Multimodal Interaction : Towards Behaviourally Established Semantic Foundations for Human-Centered AI
- 2022
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Ingår i: The 1st International Workshop on Knowledge Representation for Hybrid Intelligence (KR4HI 2022).
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Konferensbidrag (refereegranskat)abstract
- We position recent and emerging research in cognitive vision and perception addressing three key questions: (1) What kind of relational abstraction mechanisms are needed to perform (explainable) grounded inference --e.g., question-answering, qualitative generalisation, hypothetical reasoning-- relevant to embodied multimodal interaction? (2) How can such abstraction mechanisms be founded on behaviourally established cognitive human-factors emanating from naturalistic empirical observation? and (3) How to articulate behaviourally established abstraction mechanisms as formal declarative models suited for grounded knowledge representation and reasoning (KR) as part of large-scale hybrid AI and computational cognitive systems.We contextualise (1--3) in the backdrop of recent results at the interface of AI/KR, and Spatial Cognition and Computation. Our main purpose is to emphasise the importance of behavioural research based foundations for next-generation, human-centred AI, e.g., as relevant to applications in Autonomous Vehicles, Social and Industrial Robots, and Visuo-Auditory Media.
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