11. |
- Bhatt, Mehul, Professor, 1980-, et al.
(author)
-
Artificial Intelligence for Predictive and Evidence Based Architecture Design
- 2016
-
In: Proceedings of the Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16). - : AAAI press. - 9781577357605 ; , s. 4349-4350
-
Conference paper (peer-reviewed)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.
|
|
12. |
- Bhatt, Mehul, Professor, 1980-, et al.
(author)
-
Artificial Visual Intelligence : Perceptual Commonsense for Human-Centred Cognitive Technologies
- 2023
-
In: Human-Centered Artificial Intelligence. - : Springer. - 9783031243486 - 9783031243493 ; , s. 216-242
-
Book chapter (peer-reviewed)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.
|
|
13. |
|
|
14. |
- Bhatt, Mehul, Professor, 1980-, et al.
(author)
-
CLP(QS) : A Declarative Spatial Reasoning Framework
- 2011
-
In: Spatial Information Theory. - Berlin, Heidelberg : Springer. - 9783642231957 - 9783642231964 ; , s. 210-230
-
Conference paper (peer-reviewed)abstract
- We propose CLP(QS), a declarative spatial reasoning framework capable of representing and reasoning about high-level, qualitative spatial knowledge about the world. We systematically formalize and implement the semantics of a range of qualitative spatial calculi using a system of non-linear polynomial equations in the context of a classical constraint logic programming framework. Whereas CLP(QS) is a general framework, we demonstrate its applicability for the domain of Computer Aided Architecture Design. With CLP(QS) serving as a prototype, we position declarative spatial reasoning as a general paradigm open to other formalizations, reinterpretations, and extensions. We argue that the accessibility of qualitative spatial representation and reasoning mechanisms via the medium of high-level, logic-based formalizations is crucial for their utility toward solving real-world problems.
|
|
15. |
- Bhatt, Mehul, Professor, 1980-, et al.
(author)
-
Cognitive Interpretation of Everyday Activities - Toward Perceptual Narrative Based Visuo-Spatial Scene Interpretation
- 2013
-
In: 2013 Workshop on Computational Models of Narrative. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik. - 9783939897576 ; , s. 24-29
-
Conference paper (peer-reviewed)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.
|
|
16. |
- Bhatt, Mehul, Professor, 1980-
(author)
-
Cognitive media studies : Potentials for spatial cognition and AI research
- 2018
-
In: Cognitive Processing. - : Springer Berlin/Heidelberg. - 1612-4782 .- 1612-4790. ; 19:Suppl. 1, s. S6-S6
-
Journal article (other academic/artistic)abstract
- Cognitive media studies has developed as an area of research at the interface of disciplines as diverse as aesthetics, psychology, neuroscience, film theory, and cognitive science. In this context, the focus of this talk is on the foundational significance of artificial intelligence and visuo-spatial cognition and computation for the design of inte-grated analytical–empirical methods for the (multi-modal) analysis of human behaviour data vis-a-vis a range of digital visuo-auditory narrative media (e.g., narrative film). The presentation focusses on the methodological foundations and assistive technologies for systematic formalization and empirical analyses aimed at, for instance, the generation of evidence, establishing and characterizing correlates between principles for the synthesis of the moving image (e.g., from a cinematographic viewpoint), and its perceptual recipient effects and influence on observers.In the backdrop a range of completed and ongoing experiments, we emphasize the core results on the semantic interpretation of human behaviour vis-a-vis narrative film and its visuo-auditory reception. We demonstrate the manner in which AI-based models for machine coding of narrative, and relational inference and learning serves as basis to externalize explicit and inferred knowledge about embodied visuo-auditory reception, e.g., using modalities such as diagrammatic representations, natural language, complex (dynamic) data visualizations.Demonstration: The presentation will particularly showcase methods and tools developed to perform perceptual narrativisation or sensemaking with multi-modal, dynamic human-behaviour data (combining visuo-spatial imagery such as film/video, eye-tracking, head-tracking during a perception task) for a chosen set of experimental material based on existing films, as well as lab-developed experimental content.
|
|
17. |
- Bhatt, Mehul, Professor, 1980-, et al.
(author)
-
Cognitive robotics
- 2016
-
In: Journal of experimental and theoretical artificial intelligence (Print). - : Taylor & Francis Group. - 0952-813X .- 1362-3079. ; 28:5, s. 779-780
-
Journal article (peer-reviewed)
|
|
18. |
- Bhatt, Mehul, Professor, 1980-, et al.
(author)
-
Cognitive Vision and Perception : Deep Semantics Integrating AI and Vision for Reasoning about Space, Motion, and Interaction
- 2020
-
In: ECAI 2020. - : IOS Press. - 9781643681009 - 9781643681016 ; , s. 2881-2882
-
Conference paper (peer-reviewed)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.
|
|
19. |
- Bhatt, Mehul, Professor, 1980-
(author)
-
Commonsense Inference in Dynamic Spatial Systems : Epistemological Requirements
- 2010
-
In: Proceedings of the Twenty-Third International Florida Artificial Intelligence Research Society Conference (FLAIRS-23). - Menlo Park : AAAI Press. - 9781577354475 ; , s. 8-13
-
Conference paper (peer-reviewed)abstract
- We demonstrate the role of commonsense inference toward the modeling of qualitative notions of space and spatial change within a dynamic setup. The inference patterns are connected to those that are required to handle the frame problem whilst modeling inertia, and the causal minimisation of (Lin 1995) that is required to account for the ramifications of occurrences. Such patterns are both useful and necessary in order to operationalize a domain-independent qualitative spatial theory that is re-usable in arbitrary dynamic spatial systems, e.g., for spatial planning and causal explanation tasks. The illustration, grounded in the context of embedding arbitrary 'qualitative spatial calculi' within the situation calculus, utilizes topological and orientation calculi as examples.
|
|
20. |
- Bhatt, Mehul, Professor, 1980-, et al.
(author)
-
Computing Narratives of Cognitive User Experience for Building Design Analysis : KR for Industry Scale Computer-Aided Architecture Design
- 2014
-
In: Proceedings of the 14th international conference on principles of knowledge representation and reasoning. - : AAAI Press. - 9781577356578 ; , s. 508-517
-
Conference paper (peer-reviewed)abstract
- We present a cognitive design assistance system equipped with analytical capabilities aimed at anticipating architectural building design performance with respect to peoplecentred functional design goals. The paper focuses on the system capability to generate narratives of visuo-locomotive user experience from digital computer-aided architecture design (CAAD) models. The system is based on an underlying declarative narrative representation and computation framework pertaining to conceptual, geometric, and qualitative spatial knowledge. The semantics of the declarative narrative model, i.e., the overall representation and computation model, is founded on: (a) conceptual knowledge formalised in an OWL ontology; (b) a general spatial representation and reasoning engine implemented in constraint logic programming; and (c) a declaratively encoded (narrative) construction process (based on search over graph structures) implemented in answer-set programming.We emphasise and demonstrate: complete system implementation, scalability, and robust performance & integration with industry-scale architecture industry tools (e.g., Revit, Archi-CAD) & standards (BIM, IFC).
|
|