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Gesture recognition

About: Gesture recognition is a(n) research topic. Over the lifetime, 18370 publication(s) have been published within this topic receiving 350850 citation(s).

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Papers
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Open accessJournal ArticleDOI: 10.1109/TCSVT.2003.818349
Anil K. Jain1, Arun Ross2, Salil PrabhakarInstitutions (2)
Abstract: A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else. Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor. Biometric recognition, or, simply, biometrics, refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics. By using biometrics, it is possible to confirm or establish an individual's identity based on "who she is", rather than by "what she possesses" (e.g., an ID card) or "what she remembers" (e.g., a password). We give a brief overview of the field of biometrics and summarize some of its advantages, disadvantages, strengths, limitations, and related privacy concerns.

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Topics: Biometrics (56%), Speaker recognition (53%), Password (52%) ...read more

4,384 Citations


Open accessJournal ArticleDOI: 10.1109/TPAMI.2012.59
Shuiwang Ji1, Wei Xu2, Ming Yang, Kai Yu3Institutions (3)
Abstract: We consider the automated recognition of human actions in surveillance videos. Most current methods build classifiers based on complex handcrafted features computed from the raw inputs. Convolutional neural networks (CNNs) are a type of deep model that can act directly on the raw inputs. However, such models are currently limited to handling 2D inputs. In this paper, we develop a novel 3D CNN model for action recognition. This model extracts features from both the spatial and the temporal dimensions by performing 3D convolutions, thereby capturing the motion information encoded in multiple adjacent frames. The developed model generates multiple channels of information from the input frames, and the final feature representation combines information from all channels. To further boost the performance, we propose regularizing the outputs with high-level features and combining the predictions of a variety of different models. We apply the developed models to recognize human actions in the real-world environment of airport surveillance videos, and they achieve superior performance in comparison to baseline methods.

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Topics: Deep learning (58%), Convolutional neural network (56%), Artificial neural network (53%) ...read more

3,755 Citations


Open accessBook
David McNeill1Institutions (1)
15 Aug 1992-
Abstract: What is the relation between gestures and speech? In terms of symbolic forms, of course, the spontaneous and unwitting gestures we make while talking differ sharply from spoken language itself. Whereas spoken language is linear, segmented, standardized, and arbitrary, gestures are global, synthetic, idiosyncratic, and imagistic. In Hand and Mind, David McNeill presents a bold theory of the essential unity of speech and the gestures that accompany it. This long-awaited, provocative study argues that the unity of gestures and language far exceeds the surface level of speech noted by previous researchers and in fact also includes the semantic and pragmatic levels of language. In effect, the whole concept of language must be altered to take into account the nonsegmented, instantaneous, and holistic images conveyed by gestures. McNeill and his colleagues carefully devised a standard methodology for examining the speech and gesture behavior of individuals engaged in narrative discourse. A research subject is shown a cartoon like the 1950 Canary Row--a classic Sylvester and Tweedy Bird caper that features Sylvester climbing up a downspout, swallowing a bowling ball and slamming into a brick wall. After watching the cartoon, the subject is videotaped recounting the story from memory to a listener who has not seen the cartoon. Painstaking analysis of the videotapes revealed that although the research subjects--children as well as adults, some neurologically impaired--represented a wide variety of linguistic groupings, the gestures of people speaking English and a half dozen other languages manifest the same principles. Relying on data from more than ten years of research, McNeill shows thatgestures do not simply form a part of what is said and meant but have an impact on thought itself. He persuasively argues that because gestures directly transfer mental images to visible forms, conveying ideas that language cannot always express, we must examine language and gesture

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Topics: Gesture (65%), Spoken language (58%), Gesture recognition (56%) ...read more

3,529 Citations


Open accessBook
Adam Kendon1Institutions (1)
23 Sep 2004-
Abstract: 1. The domain of gesture 2. Visible action as gesture 3. Western interest in gesture from classical antiquity to the eighteenth century 4. Four contributions from the nineteenth century: Andrea de Jorio, Edward Tylor, Garrick Mallery and Wilhelm Wundt 5. Gesture studies in the twentieth century: recession and return 6. Classifying gestures 7. Gesture units, gesture phrases and speech 8. Deployments of gesture in the utterance 9. Gesture and speech in semantic interaction 10. Gesture and referential meaning 11. On pointing 12. Gestures of the 'precision-grip': topic, comment and question markers 13. Two gesture families of the open hand 14. Gesture without speech: the emergence of kinesic codes 15. Gesture and sign on common ground 16. Gesture, culture and the communication economy 17. The status of gesture Appendix I. Transcription conventions Appendix II. The recordings.

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Topics: Gesture recognition (68%), Gesture (61%)

2,249 Citations


Journal ArticleDOI: 10.1109/79.911197
Abstract: Two channels have been distinguished in human interaction: one transmits explicit messages, which may be about anything or nothing; the other transmits implicit messages about the speakers themselves. Both linguistics and technology have invested enormous efforts in understanding the first, explicit channel, but the second is not as well understood. Understanding the other party's emotions is one of the key tasks associated with the second, implicit channel. To tackle that task, signal processing and analysis techniques have to be developed, while, at the same time, consolidating psychological and linguistic analyses of emotion. This article examines basic issues in those areas. It is motivated by the PKYSTA project, in which we aim to develop a hybrid system capable of using information from faces and voices to recognize people's emotions.

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Topics: Gesture recognition (50%)

2,122 Citations


Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202219
2021885
20201,220
20191,424
20181,439
20171,420

Top Attributes

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Topic's top 5 most impactful authors

Susan Goldin-Meadow

38 papers, 4K citations

Juan P. Wachs

37 papers, 629 citations

Radu-Daniel Vatavu

36 papers, 1K citations

Vassilis Athitsos

31 papers, 1.7K citations

Ayoub Al-Hamadi

29 papers, 546 citations

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