Computational Model Based on Neural Network of Visual Cortex for Human Action Recognition
Liu, Haihua1,2,3; Shu, Na1; Tang, Qiling1; Zhang, Wensheng4
2018-05-01
发表期刊IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
卷号29期号:5页码:1427-1440
文章类型Article
摘要In this paper, we propose a bioinspired model for human action recognition through modeling neural mechanisms of information processing in two visual cortical areas: the primary visual cortex (V1) and the middle temporal cortex (MT) dedicated to motion. This model, named V1-MT, is composed of V1 and MT models (layers) corresponding to their cortical areas, which are built with layered spiking neural networks (SNNs). Some neuron properties in V1 and MT, such as direction and speed selectivity, spatiotemporal inseparability, and center surround suppression, are integrated into SNNs. Based on speed and direction selectivity, V1 and MT models contain multiple SNN channels, each of which processes motion information in sequences with spatiotemporal tunings of neurons at a certain speed and different directions. Therefore, we propose two operations, input signal perceiving with 3-D Gabor filters and surround inhibition processing with 3-D differences of Gaussian functions, to perform this task according to the spatiotemporal inseparability and center surround suppression of neurons. Then, neurons are modeled with our simplified integrate-and-fire model and motion information is transformed into spike trains. Afterward, we define a new feature vector: a mean motion map computed from spike trains in all channels to represent human actions. Finally, a support vector machine is trained to classify actions represented by the feature vectors. We conducted extensive experiments on public action databases, and the results show that our model outperforms other bioinspired models and rivals the state-of-the-art approaches.
关键词Action Recognition Classical Receptive Field (Rf) Spiking Neural Networks (Snns) Surround Suppression Visual Cortex
WOS标题词Science & Technology ; Technology
DOI10.1109/TNNLS.2017.2669522
关键词[WOS]CELL RECEPTIVE-FIELDS ; BIOLOGICAL MOTION ; SPATIOTEMPORAL ORGANIZATION ; GABOR FILTERS ; VISION SENSOR ; FEATURES ; ARCHITECTURE ; ENHANCEMENT ; SUPPRESSION ; SELECTIVITY
收录类别SCI
语种英语
项目资助者National Natural Science Foundation of China(91320102 ; 60972158 ; 61432008 ; 61532006)
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000430729100003
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/22032
专题精密感知与控制研究中心_人工智能与机器学习
作者单位1.South Cent Univ Nationalities, Sch Biomed Engn, Wuhan 430074, Hubei, Peoples R China
2.Key Lab Cognit Sci State Ethn Affairs Commiss, Wuhan 430074, Hubei, Peoples R China
3.Hubei Key Lab Med Informat Anal & Tumor Diag & Tr, Wuhan 430074, Hubei, Peoples R China
4.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
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Liu, Haihua,Shu, Na,Tang, Qiling,et al. Computational Model Based on Neural Network of Visual Cortex for Human Action Recognition[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2018,29(5):1427-1440.
APA Liu, Haihua,Shu, Na,Tang, Qiling,&Zhang, Wensheng.(2018).Computational Model Based on Neural Network of Visual Cortex for Human Action Recognition.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,29(5),1427-1440.
MLA Liu, Haihua,et al."Computational Model Based on Neural Network of Visual Cortex for Human Action Recognition".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 29.5(2018):1427-1440.
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