Vision-based hand pose estimation: A review

By Ali Erol, George Bebis, Mircea Nicolescu, Richard D. Boyle, Xander Twombly. 2007

949 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering, Human-Computer Interaction

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Citations in the corpus

Feature Boosting Network For 3D Pose Estimation (2019, background): “Different aspects of human hand (and body) pose estimation have been explored in the past few years [9,27].”
Learning Human Pose Estimation Features with Convolutional Networks (2013, background): “A more general survey of the large ﬁeld of hand tracking can be found in [12].”
Training a Feedback Loop for Hand Pose Estimation (2015, methodology): “We refer to [10] for an overview of earlier work, and here we will discuss only more recent work, which can be divided into two types of approach.”
Cross-Modal Deep Variational Hand Pose Estimation (2018, background): “Capturing the 3D motion of human hands from images is a long standing problem in computer vision and related areas (cf. [5]).”
Interacting with Soli: Exploring Fine-Grained Dynamic Gesture Recognition in the Radio-Frequency Spectrum (2016, methodology): “For the version of LSTM used in this paper [7] H is implemented by the following composite function:”
Hands Deep in Deep Learning for Hand Pose Estimation (2015, background): “A good overview of earlier work is given in [6].”
Hand gesture recognition with depth images: A review (2012, methodology): “Video-based gesture recognition addresses these issues, but presents a new problem: locating the hands and segmenting them from the background in an image sequence is a non-trivial task, in particular when there are occlusions, lighting changes, rapid motion, or other skin-colored objects in a scene”
Lending A Hand: Detecting Hands and Recognizing Activities in Complex Egocentric Interactions (2015, background): “Another well-studied problem is hand pose estimation in 3D vision [9, 31], with some work starting to consider first-person data.”
Recent methods and databases in vision-based hand gesture recognition: A review (2015, methodology): “and modeling and 3D motion based pose estimation methods are eviewed in [8] (ignoring the gesture classification schemes).”
Robust Part-Based Hand Gesture Recognition Using Kinect Sensor (2013, background): “Despite lots of previous work, traditional vision-based hand gesture recognition methods [5]–[7] are still far from satisfactory for real-life applications.”
Robotic Hand Pose Estimation Based on Stereo Vision and GPU-enabled Internal Graphical Simulation (2016, background): “Estimating the pose of a multifingered hand from vision is a challenging problem that has been studied in Human-Computer Interaction (for human hands, see [11] for a review up to the year 2007) as well as in robotics (for robot hands).”
Real-Time Articulated Hand Pose Estimation Using Semi-supervised Transductive Regression Forests (2013, background): “We refer the reader to [10] for a detailed survey of earlier hand pose estimation algorithms.”
Touch-less interactive augmented reality game on vision-based wearable device (2015, background): “Recent popular touch-less solutions provide a level of spatial input in a mobile setting [15].”
Hands in action: real-time 3D reconstruction of hands in interaction with objects (2010, methodology): “Articulated tracking and reconstruction of human hands has received an increased interest within the fields of computer vision, graphics and robotics [1] and applications include learning from demonstration, rehabilitation, prosthesis development, human-computer interaction.”
Efficient model-based 3D tracking of hand articulations using Kinect (2011, methodology): “Under the taxonomy of [6], the present work is a full, model-based pose estimation method that employs a single hypothesis.”
Cascaded hand pose regression (2015, background): “Early work on hand Most early works [17, 38, 4, 2, 13, 24] use RGB images or videos.”