Hand gesture recognition with depth images: A review

By Jesus Suarez, Robin Roberson Murphy. IEEE International Symposium on Robot and Human Interactive Communication, 2012

410 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology, Human-Computer Interaction

View Paper: https://www.semanticscholar.org/paper/711c89b1e6d1a78142bece1138b4d09ed73d5105

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In Cognitive Neuroscience

In Developmental and Educational Psychology

In Human-Computer Interaction

Citations in the corpus

Self-organizing neural integration of pose-motion features for human action recognition (2015, background): “…classiﬁcation of full-body actions (Faria et al., 2014; Shan and Akella, 2014; Parisi et al., 2014c), fall detection (Rougier et al., 2011; Mastorakis and Makris, 2012; Parisi and Wermter, 2013), and recognition of hand gestures (Suarez and Murphy, 2012; Parisi et al., 2014a,b; Yanik et al., 2014).”
Human Action Recognition with Hierarchical Growing Neural Gas Learning (2014, background): “In the last four years, the prominent use of low-cost depth sensing devices such as the Kinect sensor led to a great number of vision-based applications using depth information instead of, or in combination with, color [2].”
Gesture recognition for human-robot collaboration: A review (2017, background): “The sensors only need to contact with wrist; user's hand and ﬁ ngers are released.”
Superpixel-Based Hand Gesture Recognition With Kinect Depth Camera (2015, background): “Therefore, how the depth information can be efficiently utilized and how the depth camera can be incorporated in the hand gesture recognition system is an active topic of research [17].”
3D Gestural Interaction: The State of the Field (2013, background): “Note that other surveys that have explored earlier work on 3D gesture recognition also provide useful examinations of existing techniques [8, 51–53].”
Sign Language Recognition, Generation, and Translation: An Interdisciplinary Perspective (2019, background): “In particular, some technical reviews of gesture recognition touch on sign language recognition as an application domain (e.g., [120, 87, 108, 69]).”
Hand gesture recognition with 3D convolutional neural networks (2015, methodology): “To improve classification accuracy, gesture recognition methods with multi-modal sensors were introduced [14, 21, 12, 5, 13].”
Survey on 3D Hand Gesture Recognition (2016, background): “A survey of depth-based hand segmentation techniques can be found in [19].”