2013 Second International Conference on Robot, Vision and Signal Processing最新文献_第5页

Self-Generation of Reward by Sensor Input in Reinforcement Learning 强化学习中传感器输入奖励的自生成

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.67

Kaoru Nikaido, K. Kurashige

引用次数: 2

Biologically Inspired Topological Gaussian ARAM for Robot Navigation 机器人导航的生物启发拓扑高斯ARAM

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.66

W. Chin, C. Loo

{"title":"Biologically Inspired Topological Gaussian ARAM for Robot Navigation","authors":"W. Chin, C. Loo","doi":"10.1109/RVSP.2013.66","DOIUrl":"https://doi.org/10.1109/RVSP.2013.66","url":null,"abstract":"This paper presents a neural network for online topological map construction inspired by the beta oscillations and hippocampal place cell learning. In our proposed method, nodes in the topological map represent place cells (robot location) while edges connect nodes and store robot action (i.e. orientation, direction). Our proposed method (TGARAM) comprises 2 layers: the input layer and the memory layer. The input layer collects sensory information and cluster the obtained information into a set of topological nodes incrementally. In the memory layer, the clustered information is used as a topological map where nodes are associated with actions. Then, topological nodes are clustered together into space regions to represent the environment in the memory layer. The advantages of the proposed method are that 1) it does not require high-level cognitive processes and prior knowledge which is able to work in natural environment, 2) it can process multiple sensory sources simultaneously in continuous space, and 3) it is an incremental and unsupervised learning method. Thus, topological map generated by TGARAM is utilised for path planning to constitutes a basis for robot navigation. Finally, we validate the proposed method through several experiments.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"53 1","pages":"265-269"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90362001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Kernel-Optimized Based Machine for Image Recognition 基于核优化的图像识别机器

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.29

Yun-Heng Wang, P. Fu

引用次数: 0

Road Detection Method Corresponded to Multi Road Types with Flood Fill and Vehicle Control 多道路类型填水与车辆控制的道路检测方法

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.68

Tomoya Fukukawa, Yu Maeda, K. Sekiyama, T. Fukuda

引用次数: 7

An Efficient Super Resolution Algorithm Using Simple Linear Regression 一种基于简单线性回归的高效超分辨率算法

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.71

S. Tai, Tse-Ming Kuo, Kuo-Hao Li

引用次数: 1

Principal Component Analysis Integrating Mahalanobis Distance for Face Recognition 基于马氏距离的人脸识别主成分分析

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.27

Zizhu Fan, Ming Ni, Meibo Sheng, Zejiu Wu, Baogen Xu

引用次数: 5

Trajectory Tracking Using Auto-adaptive Multi-model Filtering Method in ADS-B System 基于自适应多模型滤波的ADS-B系统轨迹跟踪

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.28

Kai-Ge Zhang, Yu-Long Qiao, Chaozhu Zhang

引用次数: 0

Compact Multi-dimensional LBP Features for Improved Texture Retrieval 改进纹理检索的紧凑多维LBP特征

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.20

N. Doshi, G. Schaefer

{"title":"Compact Multi-dimensional LBP Features for Improved Texture Retrieval","authors":"N. Doshi, G. Schaefer","doi":"10.1109/RVSP.2013.20","DOIUrl":"https://doi.org/10.1109/RVSP.2013.20","url":null,"abstract":"Content-based image retrieval has become an important research area and consequently well performing retrieval algorithms are highly sought after. Texture features are often crucial for retrieval applications to achieve high precision, while local binary pattern (LBP) based texture descriptors have been shown to work well in this context. LBP features decsribe the texture neighbourhood of a pixel using simple comparison operators, and are often calculated based on varying neighbourhood radii to provide multi-resolution texture description. Furthermore, local contrast information can be integrated into LBP leading to LBP variance (LBPV) features. In conventional LBP methods, the histograms corresponding to different radii are simply concatenated resulting in a loss of information between different resolutions and added ambiguity. In this paper, we show that multi-dimensional LBP and LBPV histograms, which preserve the relationships between scales, provide improved texture retrieval performance. To cope with the exponential increase in terms of feature length, we show that application of principal component based feature reduction leads to very compact texture descriptors with high retrieval accuracy.","PeriodicalId":6585,"journal":{"name":"2013 Second International Conference on Robot, Vision and Signal Processing","volume":"24 1","pages":"51-55"},"PeriodicalIF":0.0,"publicationDate":"2013-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77871581","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Robot Edutainment on Walking Motion of Multi-legged Robot 多足机器人行走运动的机器人教化

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.59

Noriko Takase, János Botzheim, N. Kubota

引用次数: 3

Local Invariant Shape Feature for Cartoon Image Retrieval 局部不变形状特征在卡通图像检索中的应用

2013 Second International Conference on Robot, Vision and Signal Processing Pub Date : 2013-12-10 DOI: 10.1109/RVSP.2013.31

Tiejun Zhang, Q. Han, Handan Hou, X. Niu

引用次数: 1