Qualitative Spatial Reasoning with Oriented Point Relation in 3D Space

2019 ◽  
Vol 28 (2) ◽  
pp. 325-330 ◽  
Author(s):  
Shengsheng Wang ◽  
Ruyi Dong ◽  
Wenzhuo Song ◽  
Chuangfeng Wang
Keyword(s):  
Spatial Reasoning ◽  
Qualitative Spatial Reasoning ◽  
3D Space

scholarly journals A Bit on the Right, A Bit on the Left: Towards Logical Bundle Adjustment

2020 ◽  
Vol 10 (1) ◽  
pp. 107-123
Keyword(s):  
Iterative Process ◽  
Spatial Reasoning ◽  
Bundle Adjustment ◽  
Proof Of Concept ◽  
Qualitative Spatial Reasoning ◽  
3D Space ◽  
Least Squares Adjustment ◽  
Points Of View ◽  
The One ◽  
The Right

This article proposes an innovative approach fully based on logic to determine the relative positions and orientations of objects in a scene photographed from different points of view as well as those of the cameras used to take the pictures. The proposal is absolutely not based on 2D feature extraction, projective geometry or least squares adjustment but on a logical approach based on an enumeration of simple relationships between the objects visible in the photos. It is an approach imitating a natural and unconscious reasoning that each of us makes by observing a scene: is this object more to the right than this one? And is this other one further away from me than the one who’s partially hiding it from me? It is therefore a question of approaching the problem by identifying and recognizing objects in photographs and not by measuring millions of points in space without having any idea of the object to which they belong. This article presents a ”proof of concept” based on virtual experimentation: in a discrete 3D space, a simple scene, composed of spheres of different colors and cameras, is modelled in a 3D format. In this work the positioning of the spheres and cameras is limited to a plane. Cameras are placed in the scene in order to see the spheres and then for each camera an image is generated. The application reads each image and deducts relationships between object and camera. These relationships based on the visible occlusions between the projections of the objects onto the photographs, are formalized according to Allen’s relationships. A knowledge base is implemented to allow an iterative process of SPARQL queries for qualitative spatial reasoning leading to a set of possible solutions. Finally, the system deduces the relative positions between objects and cameras and the result is imported and can be used within several photogrammetry software suites.

PLCA

2012 ◽  
pp. 63-96 ◽  
Author(s):  
Kazuko Takahashi
Keyword(s):  
Graph Theory ◽  
Computational Geometry ◽  
Spatial Data ◽  
Qualitative Data ◽  
Spatial Reasoning ◽  
Research Area ◽  
Qualitative Spatial Reasoning ◽  
Research Areas ◽  
Fruitful Research ◽  
Topology Graph

This chapter describes a framework called PLCA for Qualitative Spatial Reasoning (QSR) based on the connection patterns of regions. The goal of this chapter is to provide a simple but expressive and feasible representation for qualitative data with sufficient reasoning ability. PLCA provides a symbolic representation for spatial data using simple objects. The authors of this chapter define its expression and operations on it, and show the correspondance between the expression and a figure. PLCA also provides semantical reasoning incorporated with spatial reasoning. Moreover, it can be extended to handle shapes of regions. Throughout the study, the authors discovered many topics that relate QSR to other research areas such as topology, graph theory, and computational geometry, while achieving the research goals. This indicates that QSR is a very fruitful research area.

The Integration of Qualitative Orientation and Named Distances: Application to a Qualitative Navigation Simulator

1997 ◽  
Vol 06 (04) ◽  
pp. 451-480 ◽  
Author(s):  
M. Teresa Escrig ◽  
Francisco Toledo
Keyword(s):  
Spatial Reasoning ◽  
Research Work ◽  
Human Perception ◽  
Positional Information ◽  
Qualitative Spatial Reasoning ◽  
Human Beings ◽  
Operational Model ◽  
Distance Information ◽  
Spatial Concepts ◽  
Definition Of

Human beings reason about different aspects of space (such as relative orientation, cardinal directions, distance, size and shape of objects) quite easily. With the aim of simulating human behavior, several models for these spatial concepts have been developed in the recent years. Cognitive considerations have made these frameworks qualitative, because they seem to deal better with the imprecision that human perception provides. However, an operational model to reason with all these spatial aspects in an integrated way has not been developed, up to now. The first aim of our research work has been the integration of different spatial concepts into the same spatial model which has been accomplished thanks to the definition of an operational model based on Constrain Logic Programming extended with Constraint Handling Rules. Although other aspects of space have been successfully represented by these techniques [2], in this paper we focus our attention in positional information, that is, orientation integrated with distance information. The Constraint Solver developed for managing positional information has a temporal complexity of O(n) 3, where n is the number of spatial landmarks considered in the reasoning process. The second aim of our work is to apply qualitative spatial reasoning to develop a Qualitative Navigation Simulator.

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