Advances in View-Invariant Human Motion Analysis: A Review

By Xiaofei Ji, Honghai Liu. 2010

260 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Computer Vision and Pattern Recognition

Citations in the corpus

Space-Time Representation of People Based on 3D Skeletal Data: A Review (2016, background): “Several earlier surveys were also published to review methods to recognize human poses, motions, gestures, and activities [37], [38], [39], [40], [41], [42], [43], [44], [45], [46], [47], [48], as well as their applications [49], [50].”
View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data (2017, background): “Researchers have paid much attention to this issue and designed view-invariant approaches for action recognition from color videos [16, 30, 3, 32, 20, 7, 33, 41, 23, 15, 22, 43, 44, 25, 49, 29, 8].”
Human Action Recognition With Video Data: Research and Evaluation Challenges (2014, background): “Using human body as reference helps to characterize actions in relative terms rather than absolute, but main concern is that inferring accurate 3-D poses from the 2-D images or video frames is difficult due to the large number of parameters that needs to be estimated, and perspective projection invo”
Action recognition on motion capture data using a dynemes and forward differences representation (2014, background): “Surveys of activity recognition approaches on such data can be found in [6], [7] and [8].”
A survey of video datasets for human action and activity recognition (2013, background): “Contents lists available at SciVerse ScienceDirect Computer Vision and Image Understanding journal homepage: www.elsevier .com/ locate/cviu A survey of video datasets for human action and activity recognition q Jose M. Chaquet a,⇑, Enrique J. Carmona a, Antonio Fernández-Caballero b a Dpto. de Intel”
Video-Based Abnormal Human Behavior Recognition—A Review (2012, background): “Very recent surveys of vision-based human action recognition [31], [42], [43] emphasize 3-D pose from individual image in a sequence, while the authors of [44] and [45]”
A survey on still image based human action recognition (2014, background): “Thus the prevailing spatiotemporal features for video-based action analysis are not appropriate for still image-based action recognition.”
3D Human pose estimation: A review of the literature and analysis of covariates (2016, background): “For instance, a review on viewinvariant pose representation and estimation is offered by Ji and Liu [32].”
Monocular human pose estimation: A survey of deep learning-based methods (2020, background): “The surveys (Aggar-wal and Cai, 1999; Gavrila, 1999; Poppe, 2007; Ji and Liu, 2010; Moeslund et al., 2011) reviewed the early work of human motion analysis in many aspects (e.g., detection and tracking, pose estimation, recognition) and described the relation be-tween human pose estimation and…”
Fuzzy human motion analysis: A review (2014, background): “This problem has received increasing attention in the HMA research and so me of the notable works have been reported [28, 45, 46].”
View Adaptive Neural Networks for High Performance Skeleton-Based Human Action Recognition (2018, background): “Some attempts have been made in previous works to overcome the view variation problem for robust action recognition [3], [8], [9], [14], [15], [19], [24], [26], [31], [36], [37], [39], [40], [50], [52], [53], [60].”
Deep Learning-based Human Pose Estimation: A Survey (2020, background): “Advances in view-invariant human motion analysis: A review [7] 2010 TSMCS A review of human motion methods based on human detection, view-invariant pose representation and estimation, and behavior understanding Human pose estimation and activity recognition from multi-view videos: Comparative explor”