检索结果-内蒙古大学图书馆

1994 International Symposium on Speech, image process.ng and Neural Networks, ISSIPNN 1994

作者： Xin, Ying-Jie Zhou, Yuan-Hua Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. Shanghai China

The paper presents a new theory and method that combines topology and digital image process.ng. It is hopeful for many difficult segmentation problems. Its application for color recognition of geographic maps is also ... 详细信息

ISBN: (纸本)078031865X

关键词： image process.ng

来源：评论

学校读者我要写书评

暂无评论

3D object recognition using qualitative features

3D object recognition using qualitative features

引用

1994 International Symposium on Speech, image process.ng and Neural Networks, ISSIPNN 1994

作者： Gu, Siyang Shi, Pengfei Li, Jiegu Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. Shanghai200030 China

ISBN: (纸本)078031865X

We present a vision system that can be to recognize 3D objects. Surfaces are characterized by surface curvature. Qualitative features are shown to be effective in pruning the search space of possible scene interpretations explored by the recognition and localization technique. Within this paradigm, we implemented a system which extracts planar patches, and patches of quadrics of revolution from a depth map. Reconstructed features are indexed into a model database to verify object hypotheses using the Hough technique. Our approach is surface based and is not sensitive to noise or occlusion. © 1994 IEEE.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Fingerprint preclassification using key-points

Fingerprint preclassification using key-points

引用

1994 International Symposium on Speech, image process.ng and Neural Networks, ISSIPNN 1994

作者： Shan, Ying Shi, Peng Fei Li, Jie Gu Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. Shanghai200030 China

ISBN: (纸本)078031865X

A new idea of fingerprint preclassification named the key-point recognition method (KMF) is proposed which only pays attention to whether there is a general feature key-point in a certain area and takes no notice of what the feature is. Using this method, an automatic fingerprint recognition system has been developed, which is characterized by fewer requirements imposed on the preprocess.ng, lower sensitivity to the noise, higher capacity and parallelism being compared with other traditional ones. The system can list out the most promising fingerprints as a preclassifier. © 1994 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Speaker normalization by input space optimization for continuous density hidden Markov models

Speaker normalization by input space optimization for contin...

引用

1994 International Symposium on Speech, image process.ng and Neural Networks, ISSIPNN 1994

作者： Wu, Jianxiong Qi, Zeyu Chan, Chorkin Li, Jiegu Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. Shanghai China Department of Computer Science Universdy of Hong Kong Hong Kong

ISBN: (纸本)078031865X

This paper proposes a novel method of speaker normalization by means of input space optimization for continuous density hidden Markov models (CDHMM). The parameters of a linear feature transformation function are so determined that, together with the previously trained CDHMM parameters, a mis-classification cost function is minimized for the normalizing data set. Preliminary experimental results on the task of sex adaptation for speaker-independent stop consonant discrimination, evaluated from the DARPA TIMIT speech database, demonstrates the effectiveness of the proposed method. © 1994 IEEE.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Car plate detection using cascaded tree-style learner based on hybrid object features

Car plate detection using cascaded tree-style learner based ...

引用

IEEE International Conference on Video and Signal Based Surveillance 2006, AVSS 2006

作者： Wu, Qiang Zhang, Huaifeng Jia, Wenjing He, Xiangjian Yang, Jie Hintz, Tom Computer Vision Research Group University of Technology Sydney PO Box 123 Broadway NSW 2007 Australia Inst. of Image Process. and Pattern Recognition Shanghai Jiaotong Univ. China

ISBN: (纸本)0769526888

Car plate detection is a key component in automatic license plate recognition system. This paper adopts an enhanced cascaded tree style learner framework for car plate detection using the hybrid object features including the simple statistical features and Harr-like features. The statistical features are useful for simplifying the process.on cascade classifier. The cascaded tree-style detector design will further reduce the false alarm and the false dismissal while retaining a high detection ratio. The experimental results obtained by the proposed algorithm exhibit the encouraging performance. © 2006 IEEE.

关键词： Object recognition

来源：评论

学校读者我要写书评

暂无评论

Small target detection using an optimization-based filter

Small target detection using an optimization-based filter

引用

IEEE International Conference on Acoustics, Speech and Signal process.ng

作者： K. Xie K. Fu T. Zhou J. Yang Q. Wu X. He Inst. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. Shanghai China

ISBN: (纸本)9781467369985

Small target detection is a critical problem in the Infrared Search And Track (IRST) system. Although it has been studied for years, there are some challenges remained, e.g. cloud edges and horizontal lines are likely to cause false alarms. This paper proposes a novel method using an optimization-based filter to detect infrared small target in heavy clutter. First, we design a certain pixel area as active area. Second, a weighted quadratic cost function is performed in the active area. Finally, a filter based on statistics of active area is derived from the cost function. Our method could preserve heterogeneous area, meanwhile, remove target region. Experimental results show our method achieves satisfied performance in heavy clutter.

关键词： active area area statistics heavy clutter optimization-based filter small target detection Object detection useful area Filters Cost functions clutter

来源：评论

学校读者我要写书评

暂无评论

Saliency Propagation from Simple to Difficult

Saliency Propagation from Simple to Difficult

引用

IEEE Conference on Computer Vision and pattern recognition

作者： Chen Gong Dacheng Tao Wei Liu S. J. Maybank Meng Fang Keren Fu Jie Yang Inst. of Image Process. & Pattern Recognition Shanghai Jiao Tong Univ. Shanghai China

ISBN: (纸本)9781467369657

Saliency propagation has been widely adopted for identifying the most attractive object in an image. The propagation sequence generated by existing saliency detection methods is governed by the spatial relationships of image regions, i.e., the saliency value is transmitted between two adjacent regions. However, for the inhomogeneous difficult adjacent regions, such a sequence may incur wrong propagations. In this paper, we attempt to manipulate the propagation sequence for optimizing the propagation quality. Intuitively, we postpone the propagations to difficult regions and meanwhile advance the propagations to less ambiguous simple regions. Inspired by the theoretical results in educational psychology, a novel propagation algorithm employing the teaching-to-learn and learning-to-teach strategies is proposed to explicitly improve the propagation quality. In the teaching-to-learn step, a teacher is designed to arrange the regions from simple to difficult and then assign the simplest regions to the learner. In the learning-to-teach step, the learner delivers its learning confidence to the teacher to assist the teacher to choose the subsequent simple regions. Due to the interactions between the teacher and learner, the uncertainty of original difficult regions is gradually reduced, yielding manifest salient objects with optimized background suppression. Extensive experimental results on benchmark saliency datasets demonstrate the superiority of the proposed algorithm over twelve representative saliency detectors.

关键词： Teachers region of an image propagation Propagation image invariant image dilation

来源：评论

学校读者我要写书评

暂无评论

Fingerprint preclassification using key-points

Fingerprint preclassification using key-points

引用

International Symposium on Speech, image process.ng and Neural Networks

作者： Ying Shan Peng Fei Shi Jie Gu Li Inst. of Image Process. & Pattern Recognition Shanghai Jiaotong Univ. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

ISBN: (纸本)078031865X

关键词： Fingerprint recognition Equations Lattices Labeling Supervised learning Energy measurement Frequency measurement Brightness Convergence Hamming distance

来源：评论

学校读者我要写书评

暂无评论

Research on procedure of knowledge representation using image stripe feature in pattern discovery

引用

Zidonghua Xuebao/Acta Automatica Sinica 2001年第1期27卷 31-38页

作者： Pang, S.N. Li, J.G. Yang, J. Image Process. and Recognition Inst. Shanghai Jiaotong Univ. Shanghai 200030 China

It is obvious that if a 2D image matrix is studied in a 1D space, any image pattern will take on stripe property in different degree. This stripe feature is popularly used in pattern discovery and pattern recognition. First, we use circle resampling to get 1D data from 2D image matrix. Second, we define a triangle base and its fractal IFS (iterative function system) and then a multi-frequency analysis math model is constructed. In the end, we apply the model to different types of image analysis and image database discovery. The result indicates that the stripe feature obtained by the method is useful both in image recognition and pattern discovery.

关键词： image analysis

来源：评论

学校读者我要写书评

暂无评论

The third eye: Mining the visual cognition across multi-language communities

The third eye: Mining the visual cognition across multi-lang...

引用

18th ACM International Conference on Multimedia ACM Multimedia 2010, MM'10

作者： Liu, Chunxi Huang, Qingming Jiang, Shuqiang Xu, Changsheng Graduate University of Chinese Academy of Sciences Beijing 100049 China Key Lab. of Intell. Info. Process. Inst. of Comput. Tech. CAS Beijing 100190 China National Lab. of Pattern Recognition Institute of Automation CAS Beijing 100190 China China-Singapore Institute of Digital Media 21 Heng Mui Keng Terrace 119613 Singapore Singapore

ISBN: (纸本)9781605589336

Existing research work in the multimedia domain mainly focuses on image/video indexing, retrieval, annotation, tagging, re-ranking, etc. However, little work has been contributed to people's visual cognition. In this paper, we propose a novel framework to mine people's visual cognition across multi-language communities. Two challenges are addressed: the visual cognition representation for a specific language community, and the visual cognition comparison between different language communities. We call it "the third eye", which means that through this way people with different backgrounds can better understand the cognition of each other, and can view the concept more objectively to avoid culture conflict. In this study, we utilize the image search engine to mine the visual cognition of the different communities. The assumption is that the image semantic distribution over the search results can reflect the visual cognition of the community. When a user submits a text query, it is first translated into different languages, and fed into the corresponding image search engine ports to retrieve images from these communities. After retrieval, the obtained images are categorized into different semantic clusters automatically. Finally, inter semantic cluster ranking is employed to rank the semantic clusters according to their relationship to the query, and intra cluster ranking is used to rank the images according to their representativeness. The visual cognition difference among these language communities is achieved by comparing the different community image distributions over these semantic clusters. The experimental results are promising and show that the proposed visual cognition mining approach is effective. © 2010 ACM.

关键词： Semantics

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：