Lexical typology through similarity semantics: Toward a semantic map of motion verbs

This paper discusses a multidimensional probabilistic semantic map of lexical motion verb stems based on data collected from parallel texts (viz. translations of the Gospel according to Mark) for 100 languages from all continents. The crosslinguistic diversity of lexical semantics in motion verbs is illustrated in detail for the domain of `go', `come', and `arrive' type contexts. It is argued that the theoretical bases underlying probabilistic semantic maps from exemplar data are the isomorphism hypothesis (given any two meanings and their corresponding forms in any particular language, more similar meanings are more likely to be expressed by the same form in any language), similarity semantics (similarity is more basic than identity), and exemplar semantics (exemplar meaning is more fundamental than abstract concepts)

Cultural-based visual expression: Emotional analysis of human face via Peking Opera Painted Faces (POPF)

© 2015 The Author(s) Peking Opera as a branch of Chinese traditional cultures and arts has a very distinct colourful facial make-up for all actors in the stage performance. Such make-up is stylised in nonverbal symbolic semantics which all combined together to form the painted faces to describe and symbolise the background, the characteristic and the emotional status of specific roles. A study of Peking Opera Painted Faces (POPF) was taken as an example to see how information and meanings can be effectively expressed through the change of facial expressions based on the facial motion within natural and emotional aspects. The study found that POPF provides exaggerated features of facial motion through images, and the symbolic semantics of POPF provides a high-level expression of human facial information. The study has presented and proved a creative structure of information analysis and expression based on POPF to improve the understanding of human facial motion and emotion

Grounding the Lexical Semantics of Verbs in Visual Perception using Force Dynamics and Event Logic

This paper presents an implemented system for recognizing the occurrence of events described by simple spatial-motion verbs in short image sequences. The semantics of these verbs is specified with event-logic expressions that describe changes in the state of force-dynamic relations between the participants of the event. An efficient finite representation is introduced for the infinite sets of intervals that occur when describing liquid and semi-liquid events. Additionally, an efficient procedure using this representation is presented for inferring occurrences of compound events, described with event-logic expressions, from occurrences of primitive events. Using force dynamics and event logic to specify the lexical semantics of events allows the system to be more robust than prior systems based on motion profile

The Semantics of Motion Verbs in Russian

Within the group of imperfective motion verbs in Russian there exists a further subdivision into determinate and indeterminate verbs. Traditionally the distinction is said to lie in the direction of motion the verbs encode: motion in one direction or in different directions. In this paper I am going to argue that this distinction is not enough. I will claim that determinate verbs encode singular eventualities and indeterminate verbs are pluractional. Thus in the normal case, imperfective verbs are plural predicates which include singular and plural events in their denotations, in the case of motion verbs, imperfective denotations are subdivided into a singular and a pluractional predicate

Intrarater Agreement of Elbow Extension Range of Motion in the Upper Limb Neurodynamic Test 1 Using a Smartphone Application

To estimate the intrarater agreement of the Compass application of a smartphone in the assessment of elbow extension range of motion (EE-ROM) at pain onset and maximum tolerable point during the Upper Limb Neurodynamic Test 1 (ULNT1).info:eu-repo/semantics/publishedVersio

Movement of "Nami" and "Nagare" in Event Structure Metaphor: On the Conceptualization of Social Activities

The study examines metaphoric expressions describing social activities in terms of the motion of water using the Event Structure Metaphor and Frame Semantics perspectives. First, we proposed two sub-types of manner of motion within the Motion Frame: animal-like motion and vehicle-like motion, and these characterize the semantics of nami (“wave”) and nagare (“flow”), respectively. Second, we demonstrated that this distinction in the manner of motion can be understood as exhibiting different readings of the two words, both literally and metaphorically in actual contexts, where they occur in relation with verbs of motion signifying a Force-Dynamic relationship between the moving object and the perceiver in a motion event

Towards automatic extraction of expressive elements from motion pictures : tempo

This paper proposes a unique computational approach to extraction of expressive elements of motion pictures for deriving high level semantics of stories portrayed, thus enabling better video annotation and interpretation systems. This approach, motivated and directed by the existing cinematic conventions known as film grammar, as a first step towards demonstrating its effectiveness, uses the attributes of motion and shot length to define and compute a novel measure of tempo of a movie. Tempo flow plots are defined and derived for four full-length movies and edge analysis is performed leading to the extraction of dramatic story sections and events signaled by their unique tempo. The results confirm tempo as a useful attribute in its own right and a promising component of semantic constructs such as tone or mood of a film

Motion-state Alignment for Video Semantic Segmentation

In recent years, video semantic segmentation has made great progress with advanced deep neural networks. However, there still exist two main challenges \ie, information inconsistency and computation cost. To deal with the two difficulties, we propose a novel motion-state alignment framework for video semantic segmentation to keep both motion and state consistency. In the framework, we first construct a motion alignment branch armed with an efficient decoupled transformer to capture dynamic semantics, guaranteeing region-level temporal consistency. Then, a state alignment branch composed of a stage transformer is designed to enrich feature spaces for the current frame to extract static semantics and achieve pixel-level state consistency. Next, by a semantic assignment mechanism, the region descriptor of each semantic category is gained from dynamic semantics and linked with pixel descriptors from static semantics. Benefiting from the alignment of these two kinds of effective information, the proposed method picks up dynamic and static semantics in a targeted way, so that video semantic regions are consistently segmented to obtain precise locations with low computational complexity. Extensive experiments on Cityscapes and CamVid datasets show that the proposed approach outperforms state-of-the-art methods and validates the effectiveness of the motion-state alignment framework.Comment: Accepted by CVPR Workshops 202