Real-Time Multi-scale Action Detection from 3D Skeleton Data

By Amr Sharaf, Marwan Torki, Mohamed E. Hussein, Motaz Ahmad El-Saban. 2015

56 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering, 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, background): “Many other existing human representations are also based on low-level skeleton-based features [117], [118], [119], [123], [134], [139], [140], [141], [154], [157], [158], [162], [200] without modeling the hierarchy of the data.”
Skeleton-Based Online Action Prediction Using Scale Selection Network (2019, methodology): “Beside the online action prediction task, the problem of temporal action detection [22], [56], [56], [57], [58], [59], [60], [61], [62], [63],”
PKU-MMD: A Large Scale Benchmark for Continuous Multi-Modal Human Action Understanding (2017, methodology): “Most methods are designed for offline action detection [38, 31, 50].”
Online Human Action Detection using Joint Classification-Regression Recurrent Neural Networks (2016, methodology): “To localize the action, most of previous works employ a sliding window design [8,5,9,10], which divides the sequence into overlapped clips before action recognition/classiﬁcation is performed on each clip.”
Real-Time Online Action Detection Forests Using Spatio-Temporal Contexts (2016, methodology): “OAD is a challenging problem [11, 25] and even though skeleton-based approaches [1, 52, 29, 35, 26, 25] are promising, they are bounded by the time constraint that prevents combining multiple feature modalities or considering more temporal relationships.”
Transition Forests: Learning Discriminative Temporal Transitions for Action Recognition and Detection (2016, background): “A similar approach but adding multi-scale information was proposed by [20], while [17] proposed a dynamic bag of features.”
Vision-based human activity recognition: a survey (2020, methodology): “Statistical models [173] are used to describe the distributions of unstructured features over time.”
SSNet: Scale Selection Network for Online 3D Action Prediction (2018, methodology): “Beside the online action prediction task, the problem of temporal action detection [68, 73, 48, 33, 7, 53, 68, 14, 54, 16, 15, 65, 82] also copes with untrimmed videos.”