Gesture

We present a real-time bidirectional communication system that lets two people, separated by distance, experience a face-to-face conversation as if they were copresent. It is the first telepresence system that is demonstrably better than 2D videoconferencing, as measured using participant ratings (e.g., presence, attentiveness, reaction-gauging, engagement), meeting recall, and observed nonverbal behaviors (e.g., head nods, eyebrow movements). This milestone is reached by maximizing audiovisual fidelity and the sense of copresence in all design elements, including physical layout, lighting, face tracking, multi-view capture, microphone array, multi-stream compression, loudspeaker output, and lenticular display. Our system achieves key 3D audiovisual cues (stereopsis, motion parallax, and spatialized audio) and enables the full range of communication cues (eye contact, hand gestures, and body language), yet does not require special glasses or body-worn microphones/headphones. The sys...

This work addresses an example for dynamic hand signal acknowledgment by utilizing a Kinect V2. The projected plan takes oneself inspired motion (general media stream) as info, separates hand region and processes hand signal highlights, and uses these elements to perceive the motion. We projected free penmanship and our strategy remembers it progressively utilizing the proposed highlight portrayal. This proposed strategy utilizes an efficient fingertip acknowledgment approach and composing with the free hand the utilization of a fingertip. We verify our strategy on Kinect V2. On a dataset gathered from various clients, we accomplish an acknowledgment exactness of 98% for character acknowledgment. We likewise show the way that this framework can be stretched out for word list acknowledgment with solid execution and additionally arranged a dataset containing data frame of the moving video and fetching characters from the database a typical benchmark to manually written character ackno...

A learning system adaptive to learner's behavior is considered as an innovative system. The more a learning system exchanges relevant fragments of information about the learner's affective status the more it adapts to it. Following this direction, we propose an integrated learning system taking under consideration learners' emotional state in order to provide a personalized elearning system. An extended version of the IEEE Reference Model (WG) LTSA is used for this purpose. The proposed approach is based on the automatic ...

Our presentation aims at analyzing Polish and French teaching contexts of trainings in languages for specific purposes. First, we will consider the modalities for trainings in languages for specific purposes at secondary school and high school levels in order to extract features specific for educational environment in each country. Then, we will compare the results of Polish and French teaching contexts analyses to identify common and divergent points of trainings in languages for professional (specific) purpose provided in Poland and France respectively.

In today’s vibrant society, digitally-mediated communication has become a natural part of our everyday life and work communication.
In this study, we explore the gestures the interactants deployed in their face-to-face communication to modify their interactional
spaces in a hybrid digital-physical context. The effects of these practices will be analyzed through the lens of recontextualization,
which assists interactants in making meanings and reaching their communicative aims. The data were collected from six 45-minute video recordings of six groups (consisting of 4–6 undergraduate sophomores per group) engaged in task-based interactional
discussions during a reading class. We have identified three types of gestures, performed either by hand or by fingers, that modify group members’ interactional spaces in their meaning-making process. Our discussions aim to enrich the semiotic resources that underline the foundation of recontextualization, thereby expanding its theoretical reach in the highly evolving digitally-mediated world.

Questo lavoro indaga la figura del silenzio, come si sviluppa in alcuni poemi di Paul Celan. In particolare, analizza l'argumentum e silentio, un'inferenza vera basata sul tacere o sulla mancanza di risposta. In questo silenzio è in gioco la morte della lingua. La lingua tedesca, che è la lingua materna del poeta. Violentata dai nazionalsocialisti e annientata nei forni crematori. La domanda riguarda come sia possibile continuare a scrivere poesia in questa lingua, e come la poesia possa sostenere ancora il mandato etico che le impone di sottrarsi a quella violenza e all'imbarbarimento. Non solo, ma anche come sia possibile, attraverso la poesia stessa, riappropriarsi di quella lingua come lingua materna. A tale proposito, Celan propone un erschwiegene Wort, una parola che sia vinta, conquistata, strappata al silenzio dell'annientamento, e allo stesso tempo una parola silenziata: la parola silenzio. Una parola detta in silenzio che riconduca il più vicino possibile a...

This paper represents text extracting information (represented by data) from a sequence of images (video) is the main objective of Video segmentation. In order to extract and search important information from a huge amount of video data, we are focusing on extraction of texts from video. However variations of the text due to differences in text style, font, size, orientation, alignment as well as low image contrast and complex background make the problem of automatic text extraction extremely difficult and challenging job. A large number of techniques have been proposed to address this problem and the purpose of this paper is to design algorithms for each phase of extracting text from a video using java libraries and classes. Here first we frame the input video into stream of images using the Java Media Framework (JMF) with the input being a real time or a video from the database and considering the connected component analysis form. We apply preprocessing algorithms to convert the ...

Given the current COVID-19 pandemic, medical research today focuses on epidemic diseases. Innovative technology is incorporated in most medical applications, emphasizing the automatic recognition of physical and emotional states. Most research is concerned with the automatic identification of symptoms displayed by patients through analyzing their body language. The development of technologies for recognizing and interpreting arm and leg gestures, facial features, and body postures is still in its early stage. More extensive research is needed using artificial intelligence (AI) techniques in disease detection. This paper presents a comprehensive survey of the research performed on body language processing. Upon defining and explaining the different types of body language, we justify the use of automatic recognition and its application in healthcare. We briefly describe the automatic recognition framework using AI to recognize various body language elements and discuss automatic gestu...

This paper is grounded in Cognitive Linguistics (CL), which sees metonymy as a conceptual phenomenon, in which one conceptual entity (the source) provides mental access to another entity (the target) within the same conceptual domain (Radden & Kövecses 1999), as opposed to metaphor, which is seen as a mapping between different domains (Lakoff 1987). Our view on metonymy slightly deviates from the mainstream CL-approach, as we reinterpret the criterion of the single domain as an epiphenomenon of the conceptually defined contiguous relationship (Feyaerts 1999), which we take to be metonymy's categorical feature. In this contribution, we analyse the structural role of metonymy in humorous interactional sequences as they occur in the American television-series House M.D. and The Big Bang Theory. As our examples qualify as staged communicative acts, the interpretation of which involves processing meanings on different layers, we use Clark's (1996) layering model to account for the humorous uses of metonymies and to show that metonymic connections lie at the heart of pragmatic inferencing. In line withand at the same time extendingearlier work (Feyaerts & Brône 2005) on the potential of metonymic chaining to generate humorous and expressive meanings, this study demonstrates how a metonymic relationship may extend across different layers of meaning-the 'serious' discourse base space and a 'non-serious' pretence spaceto generate a humorous meaning, based on the common ground between the speakers and the audience.

This work addresses an example for dynamic hand signal acknowledgment by utilizing a Kinect V2. The projected plan takes oneself inspired motion (general media stream) as info, separates hand region and processes hand signal highlights, and uses these elements to perceive the motion. We projected free penmanship and our strategy remembers it progressively utilizing the proposed highlight portrayal. This proposed strategy utilizes an efficient fingertip acknowledgment approach and composing with the free hand the utilization of a fingertip. We verify our strategy on Kinect V2. On a dataset gathered from various clients, we accomplish an acknowledgment exactness of 98% for character acknowledgment. We likewise show the way that this framework can be stretched out for word list acknowledgment with solid execution and additionally arranged a dataset containing data frame of the moving video and fetching characters from the database a typical benchmark to manually written character ackno...

This paper presents Kinect-based vision system of mine rescue robot working in illuminous underground environment. The somatosensory system of Kinect is used to realize the hand gesture recognition involving static hand gesture and action. AK-curvature based convex detection method is proposed to fit the hand contour with polygon. In addition, the hand action is completed by using the NiTE library with the framework of hand gesture recognition. In addition, the proposed method is compared with BP neural network and template matching. Furthermore, taking advantage of the information of the depth map, the interface of hand gesture recognition is established for human machine interaction of rescue robot. Experimental results verify the effectiveness of Kinect-based vision system as a feasible and alternative technology for HMI of mine rescue robot.

This chapter presents some new approaches in hand gesture recognition from monocular and from 3D images. After introducing the main trends from literature, the chapter addresses the hand gesture recognition problem in a compositional framework. The ability of compositional methods to capture and extract semantic information from selected salient parts of the images is demonstrated for the hand gesture application. Performances on images with static hand gestures executed on uniform backgrounds rival the state of the art, while living a lot of room for further optimization and improvement. The second work reported in this chapter is focused on using multiple cues to overcome difficult problems arising when dynamic gestures are executed in front of heterogeneous backgrounds, with camouflage and sudden illumination changes. Ideas from robust estimation are integrated in the proposed approach. Finally, some preliminary results of hand gesture recognition obtained with images generated b...

This paper reviews some major trends and the recent evolution in the field of hand gesture recognition. While providing a non-exhaustive inventory of the huge amount of past research in the field, the paper reviews in more detail part based approaches, particularly those embedded in the compositional framework, an emerging dominant trend in computer vision. Several traditional and new applications are also discussed in the paper.