Chapter 13 Qualitative Spatial Representation and Reasoning

Cohn, Anthony G.; Renz, Jochen

doi:10.1016/s1574-6526(07)03013-1

Cited by 266 publications

(163 citation statements)

References 80 publications

Supporting

Mentioning

156

Contrasting

Unclassified

Order By: Relevance

“…There are many calculi defined in the field of Qualitative Spatial Reasoning [8] with many applications in high level interpretation of video data [4,3,9]. One of them is CORE-9, proposed by Cohn et al [10].…”

Section: Spatio-temporal Featuresmentioning

confidence: 99%

Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning

Sokeh

Gould

Renz

2015

Computer Vision -- ACCV 2014

Self Cite

View full text Add to dashboard Cite

Abstract. Understanding the activities taking place in a video is a challenging problem in Artificial Intelligence. Complex video sequences contain many activities and involve a multitude of interacting objects. Determining which objects are relevant to a particular activity is the first step in understanding the activity. Indeed many objects in the scene are irrelevant to the main activity taking place. In this work, we consider human-centric activities and look to identify which objects in the scene are involved in the activity. We take an activity-agnostic approach and rank every moving object in the scene with how likely it is to be involved in the activity. We use a comprehensive spatio-temporal representation that captures the joint movement between humans and each object. We then use supervised machine learning techniques to recognize relevant objects based on these features. Our approach is tested on the challenging Mind's Eye dataset.

show abstract

Section: Spatio-temporal Featuresmentioning

confidence: 99%

Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning

Sokeh

Gould

Renz

2015

Computer Vision -- ACCV 2014

Self Cite

View full text Add to dashboard Cite

show abstract

“…QTC Basic and QTC Double-Cross QTC belongs to the broad research area of qualitative spatial representation and reasoning [14], from which it inherits some of its properties and tools. There are several versions of QTC, depending on the number of factors considered (e.g.…”

Section: The Qualitative Trajectory Calculusmentioning

confidence: 99%

Social distance augmented qualitative trajectory calculus for Human-Robot Spatial Interaction

Dondrup

Bellotto

Hanheide

2014

The 23rd IEEE International Symposium on Robot and Human Interactive Communication

View full text Add to dashboard Cite

Abstract-In this paper we propose to augment a wellestablished Qualitative Trajectory Calculus (QTC) by incorporating social distances into the model to facilitate a richer and more powerful representation of Human-Robot Spatial Interaction (HRSI). By combining two variants of QTC that implement different resolutions and switching between them based on distance thresholds we show that we are able to both reduce the complexity of the representation and at the same time enrich QTC with one of the core HRSI concepts: proxemics. Building on this novel integrated QTC model, we propose to represent the joint spatial behaviour of a human and a robot employing a probabilistic representation based on Hidden Markov Models. We show the appropriateness of our approach by encoding different HRSI behaviours observed in a human-robot interaction study and show how the models can be used to represent and classify these behaviours using social distance-augmented QTC.

show abstract

“…In order to reduce the space domain and focus only on those terms relevant to HRSI, we adopt the well-defined set of symbols and relations provided by QTC, which is an elegant formalism to deal with the relative motion of two points in space [10]. QTC belongs to the broad research area of qualitative spatial representation and reasoning, inheriting some of its properties and tools [11]. There are several versions of QTC, depending on the number of factors considered (e.g.…”

Section: The Qualitative Trajectory Calculusmentioning

confidence: 99%

Qualitative Design and Implementation of Human-Robot Spatial Interactions

Bellotto

Hanheide

Weghe

2013

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Abstract. Despite the large number of navigation algorithms available for mobile robots, in many social contexts they often exhibit inopportune motion behaviours in proximity of people, often with very "unnatural" movements due to the execution of segmented trajectories or the sudden activation of safety mechanisms (e.g., for obstacle avoidance). We argue that the reason of the problem is not only the difficulty of modelling human behaviours and generating opportune robot control policies, but also the way human-robot spatial interactions are represented and implemented. In this paper we propose a new methodology based on a qualitative representation of spatial interactions, which is both flexible and compact, adopting the well-defined and coherent formalization of Qualitative Trajectory Calculus (QTC). We show the potential of a QTC-based approach to abstract and design complex robot behaviours, where the desired robot's motion is represented together with its actual performance in one coherent approach, focusing on spatial interactions rather than pure navigation problems.

show abstract

Chapter 13 Qualitative Spatial Representation and Reasoning

Cited by 266 publications

References 80 publications

Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning

Determining Interacting Objects in Human-Centric Activities via Qualitative Spatio-Temporal Reasoning

Social distance augmented qualitative trajectory calculus for Human-Robot Spatial Interaction

Qualitative Design and Implementation of Human-Robot Spatial Interactions

Contact Info

Product

Resources

About