A Survey of Computer Vision-Based Human Motion Capture

By Thomas Baltzer Moeslund, Erik Granum. 2001

2,070 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition

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Citations in the corpus

Space-Time Representation of People Based on 3D Skeletal Data: A Review (2016, methodology): “Several earlier surveys were also published to review methods to recognize human poses, motions, gestures, and activities [35], [36], [37], [38], [39], [40], [41], [43], [47], [48], as well as their applications [42], [46], as summarized by the complete list in Table 1.”
Compositional Human Pose Regression (2017, background): “We refer the readers to [29, 41] for a detailed survey.”
Recent developments in human motion analysis (2003, background): “The latest survey of computer vision based human motion capture was presented by Moeslund and Granum [128].”
Human detection from images and videos: A survey (2016, background): “A review of the literature on human detection problem indicates that the various proposed solutions have been either based on studies of human motion analysis (see for example, [162, 104, 105, 3, 45]) or pedestrian detection in the context of driving assistance systems (see for example, [41, 42, 78,”
View Invariance for Human Action Recognition (2005, background): “Keywords: human action recognition, 2D invariance, invariance space trajectories”
View independent human body pose estimation from a single perspective image (2004, background): “Good starting points for understanding the applications, specific problems and solution strategies are survey papers, recent ones being [14] and [8].”
The humanID gait challenge problem: data sets, performance, and analysis (2005, background): “A more recent, extensive survey [10] looks at more than 130 publications in computer vision-based human motion analysis and classifies them based on the issues addressed: Initialization (eight publications), tracking (48 publications), pose estimation (64 publications), and recognition (16…”
Recognizing Daily and Sports Activities in Two Open Source Machine Learning Environments Using Body-Worn Sensor Units (2014, background): “One such approach is to use sensing systems fixed to the environment, such as vision systems with multiple video cameras [2] [3] [4] [5].”
Towards 3D Human Pose Estimation in the Wild: A Weakly-Supervised Approach (2017, background): “Human pose estimation has been studied considerably in the past [16, 23], and it is beyond the scope of this paper to provide a complete overview of the literature.”
View-Invariant Action Recognition from Point Triplets (2009, background): “this purpose, we introduce the idea that the motion of an articulated body can be decomposed into rigid motions of planes defined by triplets of body points.”
Vision-based human motion analysis: An overview (2007, background): “This means that pose recognition, which is classifying the pose to one of a limited number of classes, and gesture recognition, which is interpreting the movement over time, are not discussed in this overview.”
Nonlinear Body Pose Estimation from Depth Images (2005, background): “An overview of markerless motion capture systems and algorithms is given in [7].”
Tracking multiple humans in complex situations (2004, background): “Much work has been done on estimating human body postures in the context of video motion capture (a recent review is available in [26]).”