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In this paper, we present a framework abstracting motion by creating a qualitative representation of classes describing motion,
and use the continuity constraints implicitly embedded in the semantics of these classes to create a framework that enables
plausible reasoning about them. In particular, we propose a topology-based calculus of motion whos...
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... [11], six mutually exclusive classes have been formulated. They are leave(z, x, y), reach(z, x, y), hit (z, x, y), cross(z, x, y), internal (z, x, y) and external (z, x, y) representing in each case the motion class that holds between two spatio-temporal moving regions x and y during interval z. Figure 4 shows the six classes and is read as follows. The horizontal axis represents the spatial extent of the region and the vertical axis represents the temporal evolution. ...
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Citations
... Examples of qualitative approaches are the Region Connection Calculus (Randell et al. 1992), the 9-intersection model (Egenhofer and Franzosa 1991) and REMO (Laube et al. 2004). In the past decades, a continuing interest in qualitative approaches can be observed (Muller 2002;Ibrahim and Tawfik 2007;Kurata and Egenhofer 2009) with, for example, the extension of the 9-intersection model to include three-dimensional relations (Billen and Zlatanova 2003) and region-region relations (Egenhofer 2010). The main advantage of these qualitative approaches is that they provide simplified information that does not require the interpretation of complex datasets (e.g. a combination of 3 D kinematic, kinetic, and often EMG time series) and/or numerous quantitative indicators. ...
The Qualitative Trajectory Calculus (QTC) is a qualitative spatio-temporal calculus for describing interactions between moving point objects. So far, it remained unclear whether QTC is useful for describing subtle differences, such as between the movements of different parts of a human body. We tested the applicability of QTC to detect differences in the gait patterns of children with or without Developmental Coordination Disorder (DCD). We found that using a combination of three markers (i.e. ankle, toe and trochanter), QTC can achieve a high classification accuracy (i.e. 83.3%) of classifying subjects correctly to either the DCD group or the control group.
... In qualitative reasoning, however, considerable work has focused on the formalisation of motion, or moving objects in particular. Some examples are Muller (2002), Ibrahim (2007, , and Kurata & Egenhofer (2009). These approaches have in common that they rely on topological models such as the Region Connection ...
... A mereotopological approach is extend to define spatiotemporal relations and a notation of temporal slice is used, where temporal slice is called an episode of history for a given interval [15,16]. The primitive events can be defined using the Allen's temporal logic and defining relation holds(P,i) (property P holds during the time interval i) [17]. ...
... = seq eve(holds(M(XY, t 1 )) ∧ holds(D(XY, t 2 )) ∧ holds(M(XY, t 3 ))). (16) ...
Defining spatiotemporal relations and modeling motion events are emerging issues of current research. Motion events are the subclasses of spatiotemporal relations, where stable and unstable spatio-temporal topological relations and temporal order of occurrence of a primitive event play an important role. In this paper, we proposed a theory of spatio-temporal relations based on topological and orientation perspective. This theory characterized the spatiotemporal relations into different classes according to the application domain and topological stability. This proposes a common sense reasoning and modeling motion events in diverse application with the motion classes as primitives, which describe change in orientation and topological relations model. Orientation information is added to remove the locative symmetry of topological relations from motion events, and these events are defined as a systematic way. This will help to improve the understanding of spatial scenario in spatiotemporal applications.
... These approaches, unfortunately, don't take ontological commitment very serious or are based on representational artifacts which do not follow the principles of ontological realism [12]. The Motion Classes (MC) paradigm [13] which builds further on Region Connection Calculus (RCC) [14] to describe motions do not suffer from this. RCC describes how two regions are spatially located in relation to each other, thereby recognizing eight relations (Fig.2). ...
... Five more distinct classes can be defined through pair-wise combination of the nine basic motions: HIT-SPLIT, PERIPHERAL-REACH, PERIPHERAL-LEAVE, REACH-LEAVE, and LEAVE-REACH. The 76 (9 2 In the same way as RCC calculus uses tables to list the possible configurations for region pair (x,z) when the RCC-relations for the pairs (x,y) and (y,z) are known, so provides MC tables for what motion classes are possible for the pair (x,z) when the motion classes for (x,y) and (y,z) are known [13]. MC, in addition to being a representational framework for motion, can also be used as the semantic underpinning for motion verbs. ...
platform able to detect operationally significant activity in videos is being developed. The goal is to describe such activity semi-automatically in terms of verb phrases mapped to a realism-based ontology that can be used to infer and even predict further activities that are not directly visible. We describe how Region Connection Calculus and its derivative, Motion Class Calculus, can be used together to link the spatiotemporal changes that pixel-aggregates undergo in video-displays to the corresponding changes of the objects in reality that were recorded and to linguistic descriptions thereof. We discuss how Ontological Realism can be used as a safeguard to drawing such correspondences naively.
... 2. The States: The set of states Q is the set of motion verbs, which linguistically describe the patterns that motion forms as two regions move with respect to each other during a given interval, changing the topological relations that hold between them accordingly. Using the RCC8 relations, [11] formulates a set of patterns describing the motion of a moving object x with respect to another moving object y during some interval [t, t + Δ]. We will use this set, MC, as the set of states for HMM stt . ...
... Each intersection of a row and a column presents the resulting motion class mc i when the corresponding RCC8 relations at the beginning and end of the interval hold. Elements of MC continuity properties similar to those of RCC8, and hence, possess a conceptual neighborhood structure [11]. 3. ...
... being the one during which verb mc i was known to be true. The likelihood function, in this case, yields the number of ways for which verb mc j can immediately follow verb mc i , which is called, according to [11], (contin pairs(mc i ,mc j )). ...
We present a Hidden Markov Model that uses qualitative order of magnitude probabilities for its states and transitions. We
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it to build high-level natural language description of change. We use the resulting model to show an example of foreseen usage
of well-known prediction and recognition techniques used in Hidden Markov Models to perform useful queries with the representation.
A number of qualitative calculi have been developed in order to reason about space and time. A recent trend has been the emergence of integrated spatiotemporal calculi in order to deal with dynamic phenomena such as motion. In 2004, Van de Weghe introduced the Qualitative Trajectory Calculus (QTC) as a qualitative calculus to represent and reason about moving objects. This chapter presents a general overview of the principal theoretical aspects of QTC, focusing on the two most fundamental types of QTC. It shows how QTC deals with important reasoning concepts and how calculus can be employed in order to represent raw moving object data.
The method that can deal with incomplete information is of great significance in practical applications. This paper presents a method for the qualitative path reasoning with incomplete information in VAR-Space. Specifically, the conceptual neighborhood of qualitative positions in VAR-space is defined, and based on the 1-order (or 2-order) neighbors and the rule of the continuity of movement, the incomplete data problem can be solved. The experimental results indicate that the proposed method is effective.
This paper introduces a new method for calculating distances between matrix sequences of different length. Matrix sequences are often used in spatiotemporal analysis, a field of research combining topological frameworks and temporal reasoning. The Qualitative Trajectory Calculus, a spatiotemporal calculus using matrix sequences, is used as an example in this paper. Since current approaches for comparing sequences are not suitable to calculate distances between matrix sequences of different length, a new method is proposed. The method is based on sequence alignment and uses the Levenshtein distance metric as starting point. The method is presented in general at first, followed by an application to QTC-matrix sequences and a three cushion billiards movement pattern detection example. Possible applications in expert and intelligent systems are discussed, such as human-robot interaction with multiple robots, and automated traffic analysis of (autonomous) vehicle interactions. The proposed method, however, can be applied in a broad range of domains, whenever distances need to be calculated between matrix sequences of different length.
Qualitative path is a basic concept in qualitative motion reasoning. In this paper, we propose an algorithm for reasoning the qualitative path in Voronoi-Adjacency-Relation Space. Different from the previous approach in which both the dynamic Voronoi edges and the initial position are required, our approach only needs the dynamic Voronoi edges. The basic idea is that the algorithm tracks all possible initial positions, gradually rules out the impossible situation and ultimately gets the correct path. Finally, experiments have been conducted and results show that the proposed algorithm is effective.
