检索结果-内蒙古大学图书馆

11th Asian Conference on computer vision, ACCV 2012

作者： Li, Chi Lu, Le Hager, Gregory D. Tang, Jianyu Wang, Hanzi Cognitive Science Department Xiamen University Xiamen China Imaging and Computer Vision Siemens Corporate Research Princeton NJ United States Computer Science Department Johns Hopkins University Baltimore MD United States Center for Pattern Analysis and Machine Intelligence Xiamen University China

ISBN: (纸本)9783642374302

In this paper, we exploit robust depth information with simple color-shape appearance model on single object tracking in crowd dynamic scenes. Since binocular video streams are captured from a moving camera rig, background subtraction cannot provide a reliable enhancement of region of interest. Our main contribution is a novel tracking strategy to employ explicit stereo depth to track and segment object in crowd dynamic scenes with occlusion handling. Appearance cues including color and shape play a secondary role to further extract the foreground acquired by previous depth-based segmentation. The proposed depth-driven tracking approach can largely alleviate the drifting issue, especially when the object frequently interacts with similar background in long sequence tracking. The problems caused by rapid object appearance change can also be avoided due to the stability of the depth cue. Furthermore, we propose a new, yet simple and effective depth-based scheme to cope with complete occlusion in tracking. From experiments on a large collection of challenging outdoor and indoor sequences, our algorithm demonstrates accurate and reliable tracking performance which outperforms other state-of-the-art competing algorithms. © 2013 Springer-Verlag.

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Sketch-based Facial Expression recognition for Human Figure Drawing Psychological Test

Sketch-based Facial Expression Recognition for Human Figure ...

引用

Frontiers of Information Technology (FIT)

作者： Momina Moetesum Tasneem Aslam Hassan Saeed Imran Siddiqi Uzma Masroor Bahria University Islamabad PK Center of Computer Vision and Pattern Recognition Bahria University Islamabad Pakistan Dept. of Professional Psychology Bahria University Islamabad Pakistan

Drawing tests have been long used by practitioners for early screening of a number of psychological and neurological impairments. These brain functioning tests are used by psychologists to understand feelings, personality and reactions of individuals to different circumstances. Among these, Human Figure Drawing Test (HFDT) is a popular instrument for the assessment of cognitive functioning of individuals. While the HFDT has various dimensions, the focus of this study lies on the face of the drawn figure. A computerized system that analyzes the hand-drawn facial images to extract the expressions from the image is proposed. Sketch of human face is drawn by the subject and then fed to the system, the image is then binarized and segmented into different facial components. Features (based on local binary patterns, gray level co-occurrence matrices and histogram of oriented gradients) computed from the facial components are used to train an SVM classifier to learn to distinguish between four expression classes, `happy', `sad', `angry' and `neutral'. The system evaluated on a custom developed database of sketches realized promising results. The developed system could serve as a useful module toward development of a complete automated system to score human figure drawing test.

关键词： Feature extraction Psychology Face recognition Face Databases Support vector machines Lips

来源：评论

学校读者我要写书评

暂无评论

Gabor volume based local binary pattern for face representation and recognition

Gabor volume based local binary pattern for face representat...

引用

International Conference on Automatic Face and Gesture recognition

作者： Zhen Lei Shengcai Liao Ran He Matti Pietikainen Stan Z. Li Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China Center for Biometrics and Security Research & National Laboratory of Pattern Recognition Chinese Academy of Sciences Beijing China Machine Vision Group University of Oulu Oulun yliopisto FI Finland

This paper presents a novel face representation and recognition approach. The face image is first decomposed by multi-scale and multi-orientation Gabor filters and local binary pattern (LBP) analysis is then applied on the derived Gabor magnitude responses. Different from (W.C. Zhang et al., 2005), the present method not only describes the neighboring relationship in spatial domain, but also exploit those between different scales (frequency) and orientations. Specifically, we first reformulate the Gabor magnitude responses as a 3rd-order volume and then apply LBP analysis on three orthogonal planes of the Gabor volume, named GV-LBP-TOP in short, in a hope to encode sufficient information for face representation. Further, a computationally effective version, E-GV-LBP, is proposed to depict the neighboring changes in spatial, frequency and orientation domains simultaneously. Finally, the weighted histogram intersection metric is utilized to measure the dissimilarity of faces. Experimental results on FERET and FRGC ver 2.0 databases show the significant advantages of the proposed method.

关键词： Face recognition pattern recognition Histograms Principal component analysis Independent component analysis Lighting Face detection Linear discriminant analysis Robustness Gabor filters

来源：评论

学校读者我要写书评

暂无评论

Survey on Monocular Depth Estimation for Unmanned Aerial Vehicles using Deep Learning

Survey on Monocular Depth Estimation for Unmanned Aerial Veh...

引用

IEEE International Conference on Intelligent computer Communication and Processing (ICCP)

作者： Horatiu Florea Sergiu Nedevschi Computer Science Dept. Image Processing and Pattern Recognition Research Center Technical University of Cluj-Napoca Cluj-Napoca Romania

ISBN: (纸本)9781665464383

Deep learning-based solutions for the ill-posed problem of Monocular Depth Estimation (MDE) from 2D color images have shown potential in recent years, spurring a very active field of research. Most state-of-the-art proposals focus on solving the problem in the context of automotive advanced driver assistance and/or autonomous driving systems. While presenting their own complexities and challenges, the vast majority of road environments exhibit a number of commonalities amongst themselves. The aerial domain in which modern Unmanned Aerial Vehicles (UAVs) operate is significantly different and features a large variety of possible scenes based on the specific mission carried out. The increasing number of applications for UAVs could benefit from more advanced learning-based MDE solutions for recovering 3D geometric information from the scene. In this paper, we conduct a study of existing research on the topic of MDE specifically tailored for aerial views, as well as presenting the datasets and tools currently supporting such research, high-lighting the challenges that remain. To the best of our knowledge, this is the first survey covering this field.

关键词： Deep learning Technological innovation Three-dimensional displays Roads Estimation Autonomous aerial vehicles Complexity theory

来源：评论

学校读者我要写书评

暂无评论

Robust localized multi-view subspace clustering

arXiv

引用

arXiv 2017年

作者： Fan, Yanbo Liang, Jian He, Ran Hu, Bao-Gang Lyu, Siwei National Laboratory of Pattern Recognition CASIA Center for Research on Intelligent Perception and Computing CASIA Department of Computer Science University at Albany SUNY

In multi-view clustering, different views may have different confidence levels when learning a consensus representation. Existing methods usually address this by assigning distinctive weights to different views. However, due to noisy nature of real-world applications, the confidence levels of samples in the same view may also vary. Thus considering a unified weight for a view may lead to suboptimal solutions. In this paper, we propose a novel localized multi-view subspace clustering model that considers the confidence levels of both views and samples. By assigning weight to each sample under each view properly, we can obtain a robust consensus representation via fusing the noiseless structures among views and samples. We further develop a regularizer on weight parameters based on the convex conjugacy theory, and samples weights are determined in an adaptive manner. An efficient iterative algorithm is developed with a convergence guarantee. Experimental results on four benchmarks demonstrate the correctness and effectiveness of the proposed model. Copyright © 2017, The Authors. All rights reserved.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

A Statistics Based Method of Mining Hierarchical Word Relation

A Statistics Based Method of Mining Hierarchical Word Relati...

引用

2001 International Conferences on Info-tech and Info-net

作者： Hu Xiao Wu Qinyi Zhong Yixin Pattern Recognition and Intelligence System Research Center Beijing University of Posts and Telecommunications Computer Science Dept.Beijing Institute of Technology

This paper proposes a new approach to extract topic words at different levels in any specific *** method is based on the statistic features of terms in large amount text documents:term frequency and inverse document *** experiments in Chinese have indicated that the words mined out are basically coincident with the objective ***,this approach is helpful for utilizing computer to discovery the semantic relationships between words.

关键词： Conceptual Lexicon Hierarchical Word Relation Term Frequency Inverse Document Frequency

来源：评论

学校读者我要写书评

暂无评论

Efficient Window Block Retrieval in Quadtree-Based Spatial Databases

引用

GeoInformatica 1997年第1期1.0卷 59-91页

作者： Aref, Walid G. Samet, Hanan Computer Science Department Center for Automation Research University of Maryland College Park MD 20742 United States University of Alexandria Egypt University of Maryland College Park United States Matsushita Info. Technol. Laboratory Princeton United States IBM Research Almaden CA United States University of Maryland Inst. for Advanced Computer Studies College Park MD United States ACM IEEE United States Department of Computer Science University of Maryland United States Computer Vision Laboratory Stanford University United States ACM IEEE Intl. Assoc. of Pattern Recognition

An algorithm is presented to answer window queries in a quadtree-based spatial database environment by retrieving all of the quadtree blocks in the underlying spatial database that cover the quadtree blocks that comprise the window. It works by decomposing the window operation into sub-operations over smaller window partitions. These partitions are the quadtree blocks corresponding to the window. Although a block b in the underlying spatial database may cover several of the smaller window partitions, b is only retrieved once rather than multiple times. This is achieved by using an auxiliary main memory data structure called the active border which requires O(n) additional storage for a window query of size n × n. As a result, the algorithm generates an optimal number of disk I/O requests to answer a window query (i.e., one request per covering quadtree block). A proof of correctness and an analysis of the algorithm's execution time and space requirements are given, as are some experimental results.

关键词： Active border Clipping Data structures Databases Design of algorithms Quadtree space decomposition Range query Spatial databases Window block retrieval

来源：评论

学校读者我要写书评

暂无评论

Local frequency descriptor for low-resolution face recognition

Local frequency descriptor for low-resolution face recogniti...

引用

International Conference on Automatic Face and Gesture recognition

作者： Zhen Lei Timo Ahonen Matti Pietikäinen Stan Z. Li Center of Biometrics and Security Research & National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences Beijing China Machine Vision Group University of Oulu Finland

Face recognition from low-resolution images is a common yet challenging case in real applications. Since the high-frequency information is lost in low-resolution images, it is necessary to explore robust information in the low frequency domain. In this paper, we propose an effective local frequency descriptor (LFD) for low resolution face recognition, by building upon the ideas behind local phase quantization (LPQ) and exploring both blur-invariant magnitude and phase information in the low frequency domain. The proposed descriptor is more descriptive than LPQ with more comprehensive information. In addition, a statistical uniform pattern definition method is introduced to improve the efficiency of the proposed descriptor. Experimental results on FERET and a real video database show that LFD is effective and robust for low-resolution face recognition.

关键词： Face recognition Face Image resolution Probes Robustness Histograms Databases

来源：评论

学校读者我要写书评

暂无评论

Keyword spotting for self-training of BLSTM NN based handwriting recognition systems

Keyword spotting for self-training of BLSTM NN based handwri...

引用

作者： Frinken, Volkmar Fischer, Andreas Baumgartner, Markus Bunke, Horst Computer Vision Center Autonomous University of Barcelona Edifici O 08193 Bellaterra Barcelona Spain Centre for Pattern Recognition and Machine Intelligence Concordia University 1455 de Maisonneuve Blvd West Montreal QC H3G 1M8 Canada Institute of Computer Science and Applied Mathematics University of Bern Neubrückstrasse 10 CH-3012 Bern Switzerland

The automatic transcription of unconstrained continuous handwritten text requires well trained recognition systems. The semi-supervised paradigm introduces the concept of not only using labeled data but also unlabeled data in the learning process. Unlabeled data can be gathered at little or not cost. Hence it has the potential to reduce the need for labeling training data, a tedious and costly process. Given a weak initial recognizer trained on labeled data, self-training can be used to recognize unlabeled data and add words that were recognized with high confidence to the training set for re-training. This process is not trivial and requires great care as far as selecting the elements that are to be added to the training set is concerned. In this paper, we propose to use a bidirectional long short-term memory neural network handwritten recognition system for keyword spotting in order to select new elements. A set of experiments shows the high potential of self-training for bootstrapping handwriting recognition systems, both for modern and historical handwritings, and demonstrate the benefits of using keyword spotting over previously published self-training schemes. © 2013 Elsevier Ltd. All rights reserved.

关键词： Character recognition

来源：评论

学校读者我要写书评

暂无评论

Adaptive nonlinear auto-associative modeling through manifold learning

Adaptive nonlinear auto-associative modeling through manifol...

引用

9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005

作者： Zhang, Junping Li, Stan Z. Intelligent Information Processing Laboratory Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences China National Laboratory of Pattern Recognition Center for Biometrics and Security Research Institute of Automation Beijing 100080 China

ISBN: (纸本)3540260765

We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separately and recognition thereby. Unlike traditional supervised manifold learning algorithm, the proposed ANAM algorithm has several advantages: 1) it implicitly embodies discriminant information because the suboptimal parameters of ANAM are determined based on error rate of the validation set. 2) it avoids the curse of dimensionality without loss accuracy because recognition is completed in the original space. Experiments on character and digit databases show that the advantages of the proposed ANAM algorithm. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Learning systems

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：