Gesture Recognition: A Survey

By Sunanda Mitra, T. Acharya. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews), 2007

1,017 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/80f67ec9d8005c70cb9e18cf58195c4abe32deef

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In Computer Vision and Pattern Recognition

In Human-Computer Interaction

Citations in the corpus

A Low Power, Fully Event-Based Gesture Recognition System (2017, background): “While there is a large body of work on hand gesture recognition, including many real-time systems [26, 47, 30], and a growing number of publications on event-based sensors like the DAVIS [2], ATIS [36], and DVS [22], there is very little work in the intersection of the two.”
Gesture-based Object Recognition using Histograms of Guiding Strokes (2012, background): “Mitra [9] provided a survey on the approaches of gesture recognition, ranging from statistical modeling, computer vision, pattern recognition and connectionist systems.”
EgoGesture: A New Dataset and Benchmark for Egocentric Hand Gesture Recognition (2018, background): “V ISION-BASED gesture recognition [1], [2] is an important and active field of computer vision.”
A REVIEW OF VISION BASED HAND GESTURES RECOGNITION (2009, background): “Recent researches [1, 2] in computer vision have established the importance of gesture recognition systems for the purpose of human computer interaction.”
Sequential Max-Margin Event Detectors (2014, background): “Many problems in surveillance [14], activity analysis [1], clinical monitoring [20] and human computer interaction [12] can be posed as detecting events in time series.”
Gesture Recognition: A Survey (2016, background): “For example in sign languages every word is represented using a gesture [3].”
Continuous body and hand gesture recognition for natural human-computer interaction (2012, background): “This section briefly reviews some of the most relevant work; comprehensive review articles covering the material in detail include [Aggarwal and Cai 1999; Gavrila 1999; Moeslund and Granum 2001; Moeslund et al. 2006; Poppe 2007; Erol et al. 2007; Mitra and Acharya 2007].”
Multimodal Gesture Recognition Using 3-D Convolution and Convolutional LSTM (2017, methodology): “Gesture recognition is aimed to recognize and understand meaningful movements of human bodies [5].”
Large-scale Isolated Gesture Recognition using pyramidal 3D convolutional networks (2016, background): “With the rapid development of human-computer and human-robot interaction, visual gesture recognition [1] becomes one of the central research fields of computer vision.”
Gesture Recognition Portfolios for Personalization (2014, background): “A number of gesture recognition methods have been proposed in the literature [15, 6, 13], including some which operate on the human pose estimated from the Kinect [15, 6].”
Hand Gesture Recognition Based on Computer Vision: A Review of Techniques (2020, neutral): “The main approaches to hand gesture research can be classiﬁed into the wearable glove-based sensor approach and the camera vision-based sensor approach [1,2].”
Long short term memory neural network for keyboard gesture decoding (2015, background): “For a comprehensive survey on gesture recognition, consult [16].”