This paper works on gait recognition based on capsule network and we consider two different architectures, namely matching local features at the bottom layer based on capsule network and matching mid-level features at the middle layer based on capsule network, input images such as GEI, CGI, and...
Based on these results, it is observed that the overall accuracy of proposed gait recognition architecture is better for Narrow Neural Network, The values given in Table 1 also presents that the accuracy of each class for all 11 angles is better for this classifier. Table 1. Proposed ...
Gait recognition based on capsule network. J. Vis. Commun. Image Represent. 2019, 59, 159–167. [Google Scholar] [CrossRef] Wu, Y.; Hou, J.; Su, Y.; Wu, C.; Huang, M.; Zhu, Z. Gait Recognition Based on Feedback Weight Capsule Network. In Proceedings of the 2020 IEEE 4th ...
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capsule networkgait recognitionmulti-sensorspatio-temporalIt is a challenging task to identify a person based on her/his gait patterns. State-of-the-art approaches rely on the analysis of temporal or spatial characteristics of gait, and gait recognition is usually performed on single modality data ...
In this paper, we study the designing method of deep capsule network for gait recognition. We propose to extract low-level gait dynamic features by temporal module, then design capsule layers based on human body alignment module to extract high-level gait features, then design harmonization module...
Silhouette-based gait is widely used in the current gait recognition community due to their effectiveness and efficiency, but they are subject to changes in covariate conditions. The following algorithm classifies a gait irrespective of the speed variation and covariate like back pack. Convolutional ...
Purpose-The paper aims to introduce an intelligent recognition system for viewpoint variations of gait and speech.It proposes a convolutional neural network-based capsule network(CNN-CapsNet)model and outlining the performance of the system in recognition of gait and speech variations.The proposed ...
Current methods for gait recognition have been dominated by deep learning models, notably those based on partial feature representations. In this context, we propose a novel deep network, learning to transfer multi-scale partial gait representations using capsules to obtain more discriminative gait ...
Capsule networkLong-short term memorySpatio-temporal informationHuman gait is a proven biometric trait with applications in security for authentication and disease diagnosis. However, it is one-sided to express and interpret gait data from a single point of view, which can not reflect multi-...