922 resultados para beat gesture


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De-excited dynamics of p-chlorotoluene and p-dichlorobenzene have been investigated by the femtosecond pump-probe method in a supersonic molecular beam. The yields of the parent ion and daughter ion are examined as a function of the delay time between the pump and probe laser pulses. The lifetime constants of excited p-chlorotoluene and p-dichlorobenzene are determined. Possible de-excitation mechanisms are suggested that the initially excited S-1 state is predissociative via the repulsive triplet state. The substituent effects of additional chlorine atom and methyl group are discussed. Moreover, for the first time, we observe a novel quantum beat oscillation in p-dichlorobenzene. (c) 2005 Elsevier B.V. All rights reserved.

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Cloud computing is the technology prescription that will help the UK’s National Health Service (NHS) beat the budget constraints imposed as a consequence of the credit crunch. The internet based shared data and services resource will revolutionise the management of medical records and patient information while saving the NHS millions of pounds.

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Estimation of 3D hand pose is useful in many gesture recognition applications, ranging from human-computer interaction to automated recognition of sign languages. In this paper, 3D hand pose estimation is treated as a database indexing problem. Given an input image of a hand, the most similar images in a large database of hand images are retrieved. The hand pose parameters of the retrieved images are used as estimates for the hand pose in the input image. Lipschitz embeddings of edge images into a Euclidean space are used to improve the efficiency of database retrieval. In order to achieve interactive retrieval times, similarity queries are initially performed in this Euclidean space. The paper describes ongoing work that focuses on how to best choose reference images, in order to improve retrieval accuracy.

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This paper introduces BoostMap, a method that can significantly reduce retrieval time in image and video database systems that employ computationally expensive distance measures, metric or non-metric. Database and query objects are embedded into a Euclidean space, in which similarities can be rapidly measured using a weighted Manhattan distance. Embedding construction is formulated as a machine learning task, where AdaBoost is used to combine many simple, 1D embeddings into a multidimensional embedding that preserves a significant amount of the proximity structure in the original space. Performance is evaluated in a hand pose estimation system, and a dynamic gesture recognition system, where the proposed method is used to retrieve approximate nearest neighbors under expensive image and video similarity measures. In both systems, BoostMap significantly increases efficiency, with minimal losses in accuracy. Moreover, the experiments indicate that BoostMap compares favorably with existing embedding methods that have been employed in computer vision and database applications, i.e., FastMap and Bourgain embeddings.

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A framework for the simultaneous localization and recognition of dynamic hand gestures is proposed. At the core of this framework is a dynamic space-time warping (DSTW) algorithm, that aligns a pair of query and model gestures in both space and time. For every frame of the query sequence, feature detectors generate multiple hand region candidates. Dynamic programming is then used to compute both a global matching cost, which is used to recognize the query gesture, and a warping path, which aligns the query and model sequences in time, and also finds the best hand candidate region in every query frame. The proposed framework includes translation invariant recognition of gestures, a desirable property for many HCI systems. The performance of the approach is evaluated on a dataset of hand signed digits gestured by people wearing short sleeve shirts, in front of a background containing other non-hand skin-colored objects. The algorithm simultaneously localizes the gesturing hand and recognizes the hand-signed digit. Although DSTW is illustrated in a gesture recognition setting, the proposed algorithm is a general method for matching time series, that allows for multiple candidate feature vectors to be extracted at each time step.

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In gesture and sign language video sequences, hand motion tends to be rapid, and hands frequently appear in front of each other or in front of the face. Thus, hand location is often ambiguous, and naive color-based hand tracking is insufficient. To improve tracking accuracy, some methods employ a prediction-update framework, but such methods require careful initialization of model parameters, and tend to drift and lose track in extended sequences. In this paper, a temporal filtering framework for hand tracking is proposed that can initialize and reset itself without human intervention. In each frame, simple features like color and motion residue are exploited to identify multiple candidate hand locations. The temporal filter then uses the Viterbi algorithm to select among the candidates from frame to frame. The resulting tracking system can automatically identify video trajectories of unambiguous hand motion, and detect frames where tracking becomes ambiguous because of occlusions or overlaps. Experiments on video sequences of several hundred frames in duration demonstrate the system's ability to track hands robustly, to detect and handle tracking ambiguities, and to extract the trajectories of unambiguous hand motion.

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An automated system for detection of head movements is described. The goal is to label relevant head gestures in video of American Sign Language (ASL) communication. In the system, a 3D head tracker recovers head rotation and translation parameters from monocular video. Relevant head gestures are then detected by analyzing the length and frequency of the motion signal's peaks and valleys. Each parameter is analyzed independently, due to the fact that a number of relevant head movements in ASL are associated with major changes around one rotational axis. No explicit training of the system is necessary. Currently, the system can detect "head shakes." In experimental evaluation, classification performance is compared against ground-truth labels obtained from ASL linguists. Initial results are promising, as the system matches the linguists' labels in a significant number of cases.

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To compare the incidence and timing of bone fractures in postmenopausal women treated with 5 years of adjuvant tamoxifen or letrozole for endocrine-responsive early breast cancer in the Breast International Group (BIG) 1-98 trial.

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The research project takes place within the technology acceptability framework which tries to understand the use made of new technologies, and concentrates more specifically on the factors that influence multi-touch devices’ (MTD) acceptance and intention to use. Why be interested in MTD? Nowadays, this technology is used in all kinds of human activities, e.g. leisure, study or work activities (Rogowski and Saeed, 2012). However, the handling or the data entry by means of gestures on multi-touch-sensitive screen imposes a number of constraints and consequences which remain mostly unknown (Park and Han, 2013). Currently, few researches in ergonomic psychology wonder about the implications of these new human-computer interactions on task fulfillment.This research project aims to investigate the cognitive, sensori-motor and motivational processes taking place during the use of those devices. The project will analyze the influences of the use of gestures and the type of gesture used: simple or complex gestures (Lao, Heng, Zhang, Ling, and Wang, 2009), as well as the personal self-efficacy feeling in the use of MTD on task engagement, attention mechanisms and perceived disorientation (Chen, Linen, Yen, and Linn, 2011) when confronted to the use of MTD. For that purpose, the various above-mentioned concepts will be measured within a usability laboratory (U-Lab) with self-reported methods (questionnaires) and objective indicators (physiological indicators, eye tracking). Globally, the whole research aims to understand the processes at stakes, as well as advantages and inconveniences of this new technology, to favor a better compatibility and adequacy between gestures, executed tasks and MTD. The conclusions will allow some recommendations for the use of the DMT in specific contexts (e.g. learning context).

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The Interloping Beguiler is an nineteen-minute concerto in four movements for bass clarinet solo and orchestra. The title refers to the role of the solo instrument, which continually thrusts itself into the affairs of the orchestra, deceiving and diverting the members of the orchestra away from their task of performing a "serious" orchestral composition. The bass clarinet portrays a comical, cartoon-like character whose awkward, and sometimes goofy, interjections cause chaos. Attempts are made by various members of the orchestra, especially the horns, to regain control of the work, but the bass clarinet always succeeds in its distracting antics. By the final movement of the composition, the bass clarinet has propelled the work into a cartoon-like landscape of quickly changing textures, dissonant intervals, and overlapping themes. The first movement, Introduction, sets the serious tone of the music to follow, or so it would seem. The entrance of the bass clarinet immediately changes this texture with its out-of-rhythm alternations between high and low pitches. This gesture provides a glimpse into the personality of the bass clarinet, an instrument here to mislead the members of the orchestra. Deception truly begins in the second movement, The Interloping Initiates. The bass clarinet starts the movement with a driving theme and is immediately supported by the orchestra. As the movement progresses, the bass clarinet quickly begins altering the theme, making it more playful and cartoonish. A struggle ensues between the horns and the bass clarinet, with the bass clarinet catapulting the piece into a latin-inspired section. The struggle continues through to the end of the movement. The third movement, Calm, is exactly what the title suggests. A sectional form distinguishes this movement from the second movement. Throughout Calm, the bass clarinet behaves with decorum, except for very large melodic leaps. The seed of anarchy planted by the bass clarinet in the second movement comes to fruition in the final movement, The Beguiling Builds. Here, the bass clarinet sends the work into chaos with sections recalling Looney Tunes cartoons, Hollywood western music, and children's folk songs.

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The early music revival of the late twentieth century revolutionized music with the birth of historically lnformed performance. With this revolution came a stereotype of the "early music singing voice" as small, bright, straight-toned, and unfortunately, often inferior techrucally to the mainstream opera singer. An assessment of the validity of this stereotype was made though readings of treatises and modern manuals of performance practice, and through listening to recordings. Sources on ornamentation, recitative, dance rhythm, and baroque gesture were examined, resulting in the finding that these issues are far more important to historical accuracy than are voice timbre and size. This dissertation is comprised of three historically informed performances intended to satisfy both the early music specialist and the mainstream voice teacher. Program One (May 15, 2004) is a performance of The "Peasant" Cantata, BWV 212, by J.S. Bach, with The Bach Sinfonia at the Washington Conservatory of Music. Program Two (January 29, 2005) is the role of Eurilla in a staged production of Antonio Vivaldi's serenata, Eurilla e Alcindo. The performance is a collaboration with the Baltimore-based ensemble, La Rocinante, and is conducted from the keyboard by Joseph Gascho. Program Three (March 14, 2005) is a solo recital entitled, Fairest Isle: Music of Baroque London. All three programs are documented in a digital audio format available on compact disc, with accompanying programs and notes also available in digital format.

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While the hominin fossil record cannot inform us on either the presence or extent of social and cognitive abilities that may have paved the way for the emergence of language, studying non-vocal communication among our closest living relatives, the African apes, may provide valuable information about how language originated. Although much has been learned from gestural signaling in non-human primates, we have not yet established how and why gestural repertoires vary across species, what factors influence this variation, and how knowledge of these differences can contribute to an understanding of gestural signaling's contribution to language evolution. In this paper, we review arguments surrounding the theory that language evolved from gestural signaling and suggest some important factors to consider when conducting comparative studies of gestural communication among African apes. Specifically, we propose that social dynamics and positional behavior are critical components that shape the frequency and nature of gestural signaling across species and we argue that an understanding of these factors could shed light on how gestural communication may have been the basis of human language. We outline predictions for the influence of these factors on the frequencies and types of gestures used across the African apes and highlight the importance of including these factors in future gestural communication research with primates.

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Four pigs, three with focal infarctions in the apical intraventricular septum (IVS) and/or left ventricular free wall (LVFW), were imaged with an intracardiac echocardiography (ICE) transducer. Custom beam sequences were used to excite the myocardium with focused acoustic radiation force (ARF) impulses and image the subsequent tissue response. Tissue displacement in response to the ARF excitation was calculated with a phase-based estimator, and transverse wave magnitude and velocity were each estimated at every depth. The excitation sequence was repeated rapidly, either in the same location to generate 40 Hz M-modes at a single steering angle, or with a modulated steering angle to synthesize 2-D displacement magnitude and shear wave velocity images at 17 points in the cardiac cycle. Both types of images were acquired from various views in the right and left ventricles, in and out of infarcted regions. In all animals, acoustic radiation force impulse (ARFI) and shear wave elasticity imaging (SWEI) estimates indicated diastolic relaxation and systolic contraction in noninfarcted tissues. The M-mode sequences showed high beat-to-beat spatio-temporal repeatability of the measurements for each imaging plane. In views of noninfarcted tissue in the diseased animals, no significant elastic remodeling was indicated when compared with the control. Where available, views of infarcted tissue were compared with similar views from the control animal. In views of the LVFW, the infarcted tissue presented as stiff and non-contractile compared with the control. In a view of the IVS, no significant difference was seen between infarcted and healthy tissue, whereas in another view, a heterogeneous infarction was seen to be presenting itself as non-contractile in systole.

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BACKGROUND: Parrots belong to a group of behaviorally advanced vertebrates and have an advanced ability of vocal learning relative to other vocal-learning birds. They can imitate human speech, synchronize their body movements to a rhythmic beat, and understand complex concepts of referential meaning to sounds. However, little is known about the genetics of these traits. Elucidating the genetic bases would require whole genome sequencing and a robust assembly of a parrot genome. FINDINGS: We present a genomic resource for the budgerigar, an Australian Parakeet (Melopsittacus undulatus) -- the most widely studied parrot species in neuroscience and behavior. We present genomic sequence data that includes over 300× raw read coverage from multiple sequencing technologies and chromosome optical maps from a single male animal. The reads and optical maps were used to create three hybrid assemblies representing some of the largest genomic scaffolds to date for a bird; two of which were annotated based on similarities to reference sets of non-redundant human, zebra finch and chicken proteins, and budgerigar transcriptome sequence assemblies. The sequence reads for this project were in part generated and used for both the Assemblathon 2 competition and the first de novo assembly of a giga-scale vertebrate genome utilizing PacBio single-molecule sequencing. CONCLUSIONS: Across several quality metrics, these budgerigar assemblies are comparable to or better than the chicken and zebra finch genome assemblies built from traditional Sanger sequencing reads, and are sufficient to analyze regions that are difficult to sequence and assemble, including those not yet assembled in prior bird genomes, and promoter regions of genes differentially regulated in vocal learning brain regions. This work provides valuable data and material for genome technology development and for investigating the genomics of complex behavioral traits.

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Nowadays multi-touch devices (MTD) can be found in all kind of contexts. In the learning context, MTD availability leads many teachers to use them in their class room, to support the use of the devices by students, or to assume that it will enhance the learning processes. Despite the raising interest for MTD, few researches studying the impact in term of performance or the suitability of the technology for the learning context exist. However, even if the use of touch-sensitive screens rather than a mouse and keyboard seems to be the easiest and fastest way to realize common learning tasks (as for instance web surfing behaviour), we notice that the use of MTD may lead to a less favourable outcome. The complexity to generate an accurate fingers gesture and the split attention it requires (multi-tasking effect) make the use of gestures to interact with a touch-sensitive screen more difficult compared to the traditional laptop use. More precisely, it is hypothesized that efficacy and efficiency decreases, as well as the available cognitive resources making the users’ task engagement more difficult. Furthermore, the presented study takes into account the moderator effect of previous experiences with MTD. Two key factors of technology adoption theories were included in the study: familiarity and self-efficacy with the technology.Sixty university students, invited to a usability lab, are asked to perform information search tasks on an online encyclopaedia. The different tasks were created in order to execute the most commonly used mouse actions (e.g. right click, left click, scrolling, zooming, key words encoding…). Two different conditions were created: (1) MTD use and (2) laptop use (with keyboard and mouse). The cognitive load, self-efficacy, familiarity and task engagement scales were adapted to the MTD context. Furthermore, the eye-tracking measurement would offer additional information about user behaviours and their cognitive load.Our study aims to clarify some important aspects towards the usage of MTD and the added value compared to a laptop in a student learning context. More precisely, the outcomes will enhance the suitability of MTD with the processes at stakes, the role of previous knowledge in the adoption process, as well as some interesting insights into the user experience with such devices.