Answer Set Programming Modulo `Space-Time'

We present ASP Modulo `Space-Time', a declarative representational and computational framework to perform commonsense reasoning about regions with both spatial and temporal components. Supported are capabilities for mixed qualitative-quantitative reasoning, consistency checking, and inferring compositions of space-time relations; these capabilities combine and synergise for applications in a range of AI application areas where the processing and interpretation of spatio-temporal data is crucial. The framework and resulting system is the only general KR-based method for declaratively reasoning about the dynamics of `space-time' regions as first-class objects. We present an empirical evaluation (with scalability and robustness results), and include diverse application examples involving interpretation and control tasks

Moving Object Trajectories Meta-Model And Spatio-Temporal Queries

In this paper, a general moving object trajectories framework is put forward to allow independent applications processing trajectories data benefit from a high level of interoperability, information sharing as well as an efficient answer for a wide range of complex trajectory queries. Our proposed meta-model is based on ontology and event approach, incorporates existing presentations of trajectory and integrates new patterns like space-time path to describe activities in geographical space-time. We introduce recursive Region of Interest concepts and deal mobile objects trajectories with diverse spatio-temporal sampling protocols and different sensors available that traditional data model alone are incapable for this purpose.Comment: International Journal of Database Management Systems (IJDMS) Vol.4, No.2, April 201

Enhanced tracking and recognition of moving objects by reasoning about spatio-temporal continuity.

A framework for the logical and statistical analysis and annotation of dynamic scenes containing occlusion and other uncertainties is presented. This framework consists of three elements; an object tracker module, an object recognition/classification module and a logical consistency, ambiguity and error reasoning engine. The principle behind the object tracker and object recognition modules is to reduce error by increasing ambiguity (by merging objects in close proximity and presenting multiple hypotheses). The reasoning engine deals with error, ambiguity and occlusion in a unified framework to produce a hypothesis that satisfies fundamental constraints on the spatio-temporal continuity of objects. Our algorithm finds a globally consistent model of an extended video sequence that is maximally supported by a voting function based on the output of a statistical classifier. The system results in an annotation that is significantly more accurate than what would be obtained by frame-by-frame evaluation of the classifier output. The framework has been implemented and applied successfully to the analysis of team sports with a single camera. Key words: Visua

Using spatio-temporal continuity constraints to enhance visual tracking of moving objects

We present a framework for annotating dynamic scenes involving occlusion and other uncertainties. Our system comprises an object tracker, an object classifier and an algorithm for reasoning about spatio-temporal continuity. The principle behind the object tracking and classifier modules is to reduce error by increasing ambiguity (by merging objects in close proximity and presenting multiple hypotheses). The reasoning engine resolves error, ambiguity and occlusion to produce a most likely hypothesis, which is consistent with global spatio-temporal continuity constraints. The system results in improved annotation over frame-by-frame methods. It has been implemented and applied to the analysis of a team sports video

Automatic semantic video annotation in wide domain videos based on similarity and commonsense knowledgebases

In this paper, we introduce a novel framework for automatic Semantic Video Annotation. As this framework detects possible events occurring in video clips, it forms the annotating base of video search engine. To achieve this purpose, the system has to able to operate on uncontrolled wide-domain videos. Thus, all layers have to be based on generic features. This framework aims to bridge the "semantic gap", which is the difference between the low-level visual features and the human's perception, by finding videos with similar visual events, then analyzing their free text annotation to find a common area then to decide the best description for this new video using commonsense knowledgebases. Experiments were performed on wide-domain video clips from the TRECVID 2005 BBC rush standard database. Results from these experiments show promising integrity between those two layers in order to find expressing annotations for the input video. These results were evaluated based on retrieval performance

The Justified Ontology of Time

What are we justified in asserting when constructing an ontology of time? I believe a version of Presentism to be the only justified theory. ‘Justified’ here refers exclusively to a basis of empirical and epistemological evidence. What can we assert about the metaphysics of time when we start from a justificationist epistemology? Putnam and Rietdijk argue that the relativity of simultaneity supports Eternalism. My investigation examines the strength of justification Eternalism attains from the special theory of relativity (STR) and will argue that Eternalism is not justified by STR. I will also suggest that an alternative metaphysical theory of time, Point Presentism, attains justification from STR

Topological Modelling of Grammatical and Lexical Aspect in English

It is assumed that aspect in both cases — as a process-profiling category — is analogous to the profiling of things and atemporal relations (in the sense of Langacker 1987, 1990, 2000), given the maximisation of the temporal domain in the characterisation of processes (perfective and imperfective, hence: dynamic and stative), and minimalisation of the temporal domain during the conceptualisation of things (conceptually independent entities) and atemporal relations (conceptually dependent atemporal configurations). The analogy between nouns and verbs in terms of ‘granularity’ has been so far variously addressed by Langacker (1990), Jackendoff (1991) and Talmy (2001), and also constitutes the core assumption in my research on topological modelling