Journal ArticleDOI
Ongoing human action recognition with motion capture
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TLDR
This paper presents a novel framework for recognizing streamed actions using Motion Capture (MoCap) data based on histograms of action poses, extracted from MoCap data, that are computed according to Hausdorff distance.About:
This article is published in Pattern Recognition.The article was published on 2014-01-01. It has received 135 citations till now. The article focuses on the topics: Dynamic time warping & Activity recognition.read more
Citations
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Proceedings ArticleDOI
Deep Representation Learning for Human Motion Prediction and Classification
TL;DR: The results show that deep feedforward networks, trained from a generic mocap database, can successfully be used for feature extraction from human motion data and that this representation can be used as a foundation for classification and prediction.
Journal ArticleDOI
3D skeleton-based human action classification
TL;DR: This survey highlights motivations and challenges of this very recent research area by presenting technologies and approaches for 3D skeleton-based action classification, and introduces a categorization of the most recent works according to the adopted feature representation.
Proceedings ArticleDOI
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks
TL;DR: In this article, a joint trajectory map (JTM) was proposed to encode spatio-temporal information carried in 3D skeleton sequences into multiple 2D images, referred to as Joint Trajectory Maps (jTM), and ConvNets were adopted to exploit the discriminative features for real-time human action recognition.
Journal ArticleDOI
Space-time representation of people based on 3D skeletal data
TL;DR: Skeleton-based human representations have been intensively studied and kept attracting an increasing attention, due to their robustness to variations of viewpoint, human body scale and motion speed as well as the real-time, online performance as mentioned in this paper.
Posted Content
Action Recognition Based on Joint Trajectory Maps Using Convolutional Neural Networks
TL;DR: A compact, effective yet simple method to encode spatio-temporal information carried in 3D skeleton sequences into multiple 2D images, referred to as Joint Trajectory Maps (JTM), and ConvNets are adopted to exploit the discriminative features for real-time human action recognition.
References
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Proceedings ArticleDOI
A Combined Corner and Edge Detector
Chris Harris,Mike Stephens +1 more
TL;DR: The problem the authors are addressing in Alvey Project MMI149 is that of using computer vision to understand the unconstrained 3D world, in which the viewed scenes will in general contain too wide a diversity of objects for topdown recognition techniques to work.
Journal ArticleDOI
Dynamic programming algorithm optimization for spoken word recognition
TL;DR: This paper reports on an optimum dynamic progxamming (DP) based time-normalization algorithm for spoken word recognition, in which the warping function slope is restricted so as to improve discrimination between words in different categories.
Proceedings ArticleDOI
Real-time human pose recognition in parts from single depth images
Jamie Shotton,Andrew Fitzgibbon,Mat Cook,Toby Sharp,Mark J. Finocchio,Richard E. Moore,Alex Aben-Athar Kipman,Andrew Blake +7 more
TL;DR: This work takes an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler per-pixel classification problem, and generates confidence-scored 3D proposals of several body joints by reprojecting the classification result and finding local modes.
Journal ArticleDOI
Real-time human pose recognition in parts from single depth images
Jamie Shotton,Toby Sharp,Alex Aben-Athar Kipman,Andrew Fitzgibbon,Mark J. Finocchio,Andrew Blake,Mat Cook,Richard Moore +7 more
TL;DR: This work takes an object recognition approach, designing an intermediate body parts representation that maps the difficult pose estimation problem into a simpler per-pixel classification problem, and generates confidence-scored 3D proposals of several body joints by reprojecting the classification result and finding local modes.
Journal ArticleDOI
The recognition of human movement using temporal templates
Aaron F. Bobick,James W. Davis +1 more
TL;DR: A view-based approach to the representation and recognition of human movement is presented, and a recognition method matching temporal templates against stored instances of views of known actions is developed.