A Convolutional Neural Network Hand Tracker

By Steven J. Nowlan, John C. Platt. 1994

Subfields: Computer Vision and Pattern Recognition

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Citations in the corpus

OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks (2013, background): “Many authors have proposed to use ConvNets for detection and localization with a sliding window over multiple scales, going back to the early 1990’s for multi-character strings [20], faces [30], and hands [22].”
Pedestrian Detection with Unsupervised Multi-stage Feature Learning (2012, methodology): “Supervised ConvNets have been used by a number of authors for such applications as face, hand detection [37, 29, 15, 31, 14, 36].”
Joint Training of a Convolutional Network and a Graphical Model for Human Pose Estimation (2014, background): “We show that joint training of these two model paradigms improves performance and allows us to significantly outperform existing state-of-the-art techniques.”
Recent advances in convolutional neural networks (2015, methodology): “In some early works [116], [118], [127], they use the sliding window based approaches to”
Learning Human Pose Estimation Features with Convolutional Networks (2013, background): “Examples include [14, 49, 5, 30].”
Synergistic Face Detection and Pose Estimation with Energy-Based Models (2004, background): “Yaw-error tolerance (degrees) Percentage of yaws correctly estimated”
Object Detection in 20 Years: A Survey (2019, methodology): “CNN also has been applied to other tasks such as face detection [112, 113] and hand tracking [114] of its time.”
Convolutional networks and applications in vision (2010, background): “Other experimental detection applications include hands/gesture [19], logos and text [20].”
Large-Scale FPGA-based Convolutional Networks (2011, background): “…license plates and faces in Google’s StreetView (Frome et al., 2009), or customers’ gender and age at NEC, • more experimental detection of hands/gestures (Nowlan and Platt, 1995), logos and text (Delakis and Garcia, 2008), • vision-based navigation for off-road robots: in the DARPA-sponsored…”
A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets (2021, methodology): “[85] implemented the first tracking system that tracks hand gestures in a sequence of frames using a CNN model.”
Real-Time Continuous Pose Recovery of Human Hands Using Convolutional Networks (2014, background): “images of hands tend to have many repeated local image features (for instance, ﬁngertips), ConvNets are well suited to perform feature extraction since multilayered feature banks can share common features, thereby reducing the number of required free parameters.”
Toward automatic phenotyping of developing embryos from videos (2005, background): “Since the completion of theC.elegansgenome sequence and identification of its roughly20, 000 protein-coding genes in 1998 [6], extensive research has been done on analyzing how these genes functioni vivo.”
Gradient-based learning applied to document recognition (1998, methodology): “The idea has been applied to face location [93], address block location on envelopes [94], and hand tracking in video [95].”
Multiple Instance Boosting for Object Detection (2005, methodology): “Unlike Nowlan and Platt, we maintain a cascade of detectors for maximum speed.”
Pose-Sensitive Embedding by Nonlinear NCA Regression (2010, background): “Many techniques rely on sliding-window part detectors based on color and other features applied to controlled recording conditions ([10, 39, 4, 28] to name a few, we refer to [32] for a complete survey).”
Region-Based Convolutional Networks for Accurate Object Detection and Segmentation (2016, methodology): “CNNs have been used in this way for at least two decades, typically on constrained object categories, such as faces [14], [15], hands [16], and pedestrians [17].”