检索结果-内蒙古大学图书馆

ieee/CVF conference on computer vision and pattern recognition (cvpr)

作者： Naphade, Milind Wang, Shuo Anastasiu, David C. Tang, Zheng Chang, Ming-Ching Yao, Yue Zheng, Liang Rahman, Mohammed Shaiqur Venkatachalapathy, Archana Sharma, Anuj Feng, Qi Ablavsky, Vitaly Sclaroff, Stan Chakraborty, Pranamesh Li, Alice Li, Shangru Chellappa, Rama NVIDIA Corp Santa Clara CA 95051 USA Santa Clara Univ Santa Clara CA 95053 USA SUNY Albany Albany NY 12222 USA Australian Natl Univ Canberra ACT Australia Indian Inst Technol Kanpur Kanpur Uttar Pradesh India Iowa State Univ Ames IA USA Boston Univ Boston MA 02215 USA Univ Washington Seattle WA 98195 USA Johns Hopkins Univ Baltimore MD 21218 USA

ISBN: (数字)9781665487399

ISBN: (纸本)9781665487399

the 6th edition of the AI City Challenge specifically focuses on problems in two domains where there is tremendous unlocked potential at the intersection of computer vision and artificial intelligence: Intelligent Traffic Systems (ITS), and brick and mortar retail businesses. the four challenge tracks of the 2022 AI City Challenge received participation requests from 254 teams across 27 countries. Track 1 addressed city-scale multi-target multi-camera (MTMC) vehicle tracking. Track 2 addressed natural-language-based vehicle track retrieval. Track 3 was a brand new track for naturalistic driving analysis, where the data were captured by several cameras mounted inside the vehicle focusing on driver safety, and the task was to classify driver actions. Track 4 was another new track aiming to achieve retail store automated checkout using only a single view camera. We released two leader boards for submissions based on different methods, including a public leader board for the contest, where no use of external data is allowed, and a general leader board for all submitted results. the top performance of participating teams established strong baselines and even outperformed the state-of-the-art in the proposed challenge tracks.

关键词： computer vision Mortar Urban areas Focusing Cameras Safety pattern recognition

来源：评论

学校读者我要写书评

暂无评论

A Comparison of Linearisation and the Unscented Transform for computer vision Applications

A Comparison of Linearisation and the Unscented Transform fo...

引用

27th Annual Symposium of the pattern-recognition-Association-of-South-Africa / 9th Robotics and Mechatronics conference of South Africa (Robmech)

作者： Chiu, Alexander Jones, thomas van Daalen, Corne E. Stellenbosch Univ Dept Elect & Elect Engn Stellenbosch South Africa

ISBN: (纸本)9781509033355

Accurate sensor noise propagation is critical for many computer vision and robotic applications. Several probabilistic computer vision techniques require estimates of sensor noise after it has been propagated through one or many non-linear transformations. We investigate the unscented transform as an alternative to the standard linearisation technique for uncertainty propagation in a computer vision framework. An evaluation is performed using synthetic data for two common computer vision sensors, an RGB-D sensor and stereo camera pair. the unscented transform is shown to outperform linearisation when used to estimate distributions of reconstructed, 3D points from image features. Experimental results also indicate that the unscented transform is a viable replacement for linearisation when used in a probabilistic visual odometry framework.

关键词： computer vision

来源：评论

学校读者我要写书评

暂无评论

An overview of robot vision

An overview of robot vision

引用

27th Southern African Universities Power Engineering conference (SAUPEC) / 11th Robotics and Mechatronics conference of South Africa (RobMech) / 29th Annual Symposium of pattern-recognition-Association-of-South-Africa (PRASA)

作者： van Eden, Beatrice Rosman, Benjamin CSIR Mobile Intelligent Autonomous Syst Pretoria South Africa Univ Witwatersrand Sch Comp Sci & Appl Math Johannesburg South Africa

ISBN: (纸本)9781728103693

Robot vision is an interdisciplinary field that deals with how robots can be made to gain high-level understanding from digital images or videos. Understanding an image at the pixel level often does not provide enough information for decision making and action taking. In this case, higher level semantic information that describes the image is required. this helps the robot to accomplish complex tasks that require visual understanding. For robots to add value they need to be sufficiently effective at executing tasks in different settings. Despite many impressive advances in robot vision, robots still lack the ability to function as humans do in complex environments. Importantly, this includes being able to interpret and understand the perceptual complexities of the world. Robot vision is dependant on ideas from both computer vision and machine learning. In this paper we provide a overview of the advances in these disciplines and how they contribute to robot vision.

关键词： Robot sensing systems Image classification Object recognition Object detection Visualization computer architecture

来源：评论

学校读者我要写书评

暂无评论

Pupil detection for head-mounted eye tracking in the wild: an evaluation of the state of the art

引用

MACHINE vision AND APPLICATIONS 2016年第8期27卷 1275-1288页

作者： Fuhl, Wolfgang Tonsen, Marc Bulling, Andreas Kasneci, Enkelejda Univ Tubingen Percept Engn Grp Tubingen Germany Max Planck Inst Informat Perceptual User Interfaces Grp Saarbrucken Germany

Robust and accurate detection of the pupil position is a key building block for head-mounted eye tracking and prerequisite for applications on top, such as gaze-based human-computer interaction or attention analysis. Despite a large body of work, detecting the pupil in images recorded under real-world conditions is challenging given significant variability in the eye appearance (e.g., illumination, reflections, occlusions, etc.), individual differences in eye physiology, as well as other sources of noise, such as contact lenses or make-up. In this paper we review six state-of-the-art pupil detection methods, namely ElSe (Fuhl et al. in Proceedings of the ninth biennial ACM symposium on eye tracking research&applications, ACM. New York, NY, USA, pp 123130, 2016), ExCuSe (Fuhl et al. in computer analysis of images and patterns. Springer, New York, pp 39-51, 2015), Pupil Labs (Kassner et al. in Adjunct proceedings of the 2014 ACM international joint conference on pervasive and ubiquitous computing (UbiComp), pp 1151-1160, 2014. doi: 10.1145/2638728.2641695), SET (Javadi et al. in Front Neuroeng 8, 2015), Starburst (Li et al. in computer vision and pattern recognition-workshops, 2005. ieee computer society conference on cvpr workshops. ieee, pp 79-79, 2005), and Swirski (Swirski et al. in Proceedings of the symposium on eye tracking research and applications (ETRA). ACM, pp 173-176, 2012. doi: 10.1145/2168556.2168585). We compare their performance on a large-scale data set consisting of 225,569 annotated eye images taken from four publicly available data sets. Our experimental results show that the algorithm ElSe (Fuhl et al. 2016) outperforms other pupil detection methods by a large margin, offering thus robust and accurate pupil positions on challenging everyday eye images.

关键词： Pupil detection Head-mounted eye tracking Data set computer vision Image processing

来源：评论

学校读者我要写书评

暂无评论

Design of Intelligent Database Program for an Interactive Auto-Responsive SMS-based Opinion Poll System using Triggers and Stored Procedure 27

Design of Intelligent Database Program for an Interactive Au...

引用

ieee 27th Canadian conference on Electrical and computer Engineering (CCECE)

作者： Adetiloye, Kehinde O. IEEE LaSalle CA USA

ISBN: (纸本)9781479930999

Short Message Service (SMS) has remained an integral part of the mobile phone technology, in spite of the huge evolution experienced in the technology since the last two decades, due to its wide acceptance by mobile consumers as a valuable means of exchanging and broadcasting text messages, and utilizing special applications such as SMS-based mobile-banking and SMS-based control systems. therefore, there is no gainsaying in the fact that studies and projects aimed at leveraging the mass and steady adoption of SMS will continue to emerge. In this paper, we present procedures for developing an intelligent database program for a SMS-based opinion poll system using triggers and stored procedure. the solution we propose, aside benefitting from the data security and integrity and performance optimization of using triggers and stored procedure with data in a secured Relational Database Management System (RDBMS), offers an innovative approach for incorporating intelligence in database for related applications.

关键词： SMS intelligent database opinion poll stored procedures triggers pattern recognition

来源：评论

学校读者我要写书评

暂无评论

A novel eyelash detection method for iris recognition

A novel eyelash detection method for iris recognition

引用

2005 27th Annual International conference of the Engineering in Medicine and Biology Society, ieee-EMBS 2005

作者： Yuan, Weiqi He, Wei Computer Vision Group of Information Institute Shenyang University of Technology Shenyang 110023 China

ISBN: (纸本)0780387406

Iris is often affected by the eyelash noise, when captured under unfavorable condition. Not only the iris localization of inner and outer boundaries, but also iris feature extraction can be affected by eyelash. therefore, in an iris recognition system, eyelash detection is of great importance for accurate iris recognition. Eyelash can be classified into two classes: (1) separable eyelashes (2) multiple eyelashes. the former are detected by local intensity minimum algorithm, and the latter are detected according to the template mean and standard deviation. Experimental results show that the proposed method can detect eyelash accurately. © 2005 ieee.

关键词： pattern recognition

来源：评论

学校读者我要写书评

暂无评论

Plant recognition System based on Deep Features and Color-LBP method 27

Plant Recognition System based on Deep Features and Color-LB...

引用

27th Signal Processing and Communications Applications conference (SIU)

作者： Turkoglu, Muammer Hanbay, Davut Bingol Univ Bilgisayar Muhendisligi Muhendislik Mirmarlik Fak Bingol Turkey Inonu Univ Muhendislik Fak Bilgisayar Muhendisligi Malatya Turkey

ISBN: (纸本)9781728119045

In recent years, deep learning, which is widely used in machine learning and computer vision, offers many new solutions, especially for agricultural problems. In this study, an approach based on the combination of Convolutional Neural Networks (CNN) and Color-Local Binary pattern (C-LBP) method is recommended for the determination of plant species. Deep features have been obtained from the fc6 layer of the AlexNet model, a pre-trained ESA architecture. then, LBP method is applied to each channel of color images (R, G, B). Finally, the deep features and LBP features from each color channel were combined and classified by Support Vector Machine (SVM). To test the accuracy of the proposed approach, ICL and Folio leaf data sets commonly used in the literature have been used. According to this results, accuracy rates of 98.50% and 99.48% were calculated for ICL and Folio data sets, respectively. the experimental results indicate that the proposed model achieves better accuracy compared to previous studies.

关键词： Plant recognition Deep Features AlexNet architecture Support Vector Machines Local Binary pattern

来源：评论

学校读者我要写书评

暂无评论

FgGAN: A Cascaded Unpaired Learning for Background Estimation and Foreground Segmentation 19

FgGAN: A Cascaded Unpaired Learning for Background Estimatio...

引用

19th ieee Winter conference on Applications of computer vision (WACV)

作者： Patil, Prashant W. Murala, Subrahmanyam Indian Inst Technol Ropar Comp Vis & Pattern Recognit Lab Rupnagar India

ISBN: (纸本)9781728119755

the moving object segmentation (MOS) in videos with bad weather, irregular motion of objects, camera jitter, shadow and dynamic background scenarios is still an open problem for computer vision applications. To address these issues, in this paper, we propose an approach named as Foreground Generative Adversarial Network (FgGAN) with the recent concepts of generative adversarial network (GAN) and unpaired training for background estimation and foreground segmentation. To the best of our knowledge, this is the first paper with the concept of GAN-based unpaired learning for MOS. Initially, video-wise background is estimated using GAN-based unpaired learning network (network-I). then, to extract the motion information related to foreground, motion saliency is estimated using estimated background and current video frame. Further, estimated motion saliency is given as input to the GAN-based unpaired learning network (network-II) for foreground segmentation. To examine the effectiveness of proposed FgGAN (cascaded networks I and II), the challenging video categories like dynamic background, bad weather, intermittent object motion and shadow are collected from ChangeDetection. net-2014 [26] database. the segmentation accuracy is observed qualitatively and quantitatively in terms of F-measure and percentage of wrong classification (PWC) and compared with the existing state-of-the-art methods. From experimental results, it is evident that the proposed FgGAN shows significant improvement in terms of F-measure and PWC as compared to the existing state-of-the-art methods for MOS.

关键词： Videos Estimation Motion segmentation Image segmentation Meteorology Dynamics Histograms

来源：评论

学校读者我要写书评

暂无评论

MULTI-CLASS WEAthER CLASSIFICATION FROM STILL IMAGE USING SAID ENSEMBLE MEthOD

MULTI-CLASS WEATHER CLASSIFICATION FROM STILL IMAGE USING SA...

引用

作者： Ajayi, Gbeminiyi Oluwafemi Wang Zenghui Univ South Africa Elect & Min Dept Johannesburg South Africa

ISBN: (纸本)9781728103693

In the field of computer vision, multi-class outdoor weather classification is a difficult task to perform due to diversity and lack of distinct weather characteristic or features. this research proposed a novel framework for identifying different weather scenes from still images using heterogeneous ensemble methods. Our approach is based on a method called Selection Based on Accuracy Intuition and diversity (SAID) of stacked ensemble algorithms. this involves the extraction of histogram of features from different weather scenes. the blending and boosting of different weather features using stacked ensemble algorithms increases recognition rate of different weather conditions compared to other classification and ensemble methods. the paper presents academic and practitioners a new insight into diversity of heterogeneous ensemble methods for solving the challenges of weather recognition from still images.

关键词： Stacking ensemble ensemble diversity weather identification recognition Image classification

来源：评论

学校读者我要写书评

暂无评论

Uncertain LDA: Including Observation Uncertainties in Discriminative Transforms

引用

ieee TRANSACTIONS ON pattern ANALYSIS AND MACHINE INTELLIGENCE 2016年第7期38卷 1479-88页

作者： Saeidi, Rahim Astudillo, Ramon Fernandez Kolossa, Dorothea Aalto Univ Dept Signal Proc & Acoust Espoo Uusimaa Finland INESC ID Spoken Language Syst Lab Lisbon Portugal Ruhr Univ Bochum Inst Commun Acoust Univ Str 150 Bochum Nrw Germany

Linear discriminant analysis (LDA) is a powerful technique in pattern recognition to reduce the dimensionality of data vectors. It maximizes discriminability by retaining only those directions that minimize the ratio of within-class and between-class variance. In this paper, using the same principles as for conventional LDA, we propose to employ uncertainties of the noisy or distorted input data in order to estimate maximally discriminant directions. We demonstrate the efficiency of the proposed uncertain LDA on two applications using state-of-the-art techniques. First, we experiment with an automatic speech recognition task, in which the uncertainty of observations is imposed by real-world additive noise. Next, we examine a full-scale speaker recognition system, considering the utterance duration as the source of uncertainty in authenticating a speaker. the experimental results show that when employing an appropriate uncertainty estimation algorithm, uncertain LDA outperforms its conventional LDA counterpart.

关键词： Uncertainty linear discriminant analysis LDA speaker recognition speech recognition

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：