Biologically motivated computer vision : first IEEE International Workshop, BMCV 2000, Seoul, Korea, May 15-17, 2000 : proceedings
著者
書誌事項
Biologically motivated computer vision : first IEEE International Workshop, BMCV 2000, Seoul, Korea, May 15-17, 2000 : proceedings
(Lecture notes in computer science, 1811)
Springer, c2000
大学図書館所蔵 全39件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes bibliographical references and index
内容説明・目次
内容説明
It is our great pleasure and honor to organize the First IEEE Computer Society International Workshop on Biologically Motivated Computer Vision (BMCV 2000). The workshop BMCV 2000 aims to facilitate debates on biologically motivated vision systems and to provide an opportunity for researchers in the area of vision to see and share the latest developments in state-of-the-art technology. The rapid progress being made in the field of computer vision has had a tremendous impact on the modeling and implementation of biologically motivated computer vision. A multitude of new advances and findings in the domain of computer vision will be presented at this workshop. By December 1999 a total of 90 full papers had been submitted from 28 countries. To ensure the high quality of workshop and proceedings, the program committee selected and accepted 56 of them after a thorough review process. Of these papers 25 will be presented in 5 oral sessions and 31 in a poster session. The papers span a variety of topics in computer vision from computational theories to their implementation. In addition to these excellent presentations, there will be eight invited lectures by distinguished scientists on "hot" topics. We must add that the program committee and the reviewers did an excellent job within a tight schedule.
目次
Invited Paper (1).- CBF: A New Framework for Object Categorization in Cortex.- Invited Paper (2).- The Perception of Spatial Layout in a Virtual World.- Segmentation, Detection and Object Recognition.- Towards a Computational Model for Object Recognition in IT Cortex.- Straight Line Detection as an Optimization Problem: An Approach Motivated by the Jumping Spider Visual System.- Factorial Code Representation of Faces for Recognition.- Distinctive Features Should Be Learned.- Moving Object Segmentation Based on Human Visual Sensitivity.- Invited Paper (3).- Object Classification Using a Fragment-Based Representation.- Computational Model.- Confrontation of Retinal Adaptation Model with Key Features of Psychophysical Gain Behavior Dynamics.- Polarization-Based Orientation in a Natural Environment.- Computation Model of Eye Movement in Reading Using Foveated Vision.- New Eyes for Shape and Motion Estimation.- Top-Down Attention Control at Feature Space for Robust Pattern Recognition.- A Model for Visual Camouflage Breaking.- Active and Attentive Vision.- Development of a Biologically Inspired Real-Time Visual Attention System.- Real-Time Visual Tracking Insensitive to Three-Dimensional Rotation of Objects.- Heading Perception and Moving Objects.- Dynamic Vergence Using Disparity Flux.- Invited Paper (4).- Computing in Cortical Columns: curve inference and stereo correspondence.- Invited Paper (5).- Active Vision from Multiple Cues.- Posters.- An Efficient Data Structure for Feature Extraction in a Foveated Environment.- Parallel Trellis Based Stereo Matching Using Constraints.- Unsupervised Learning of Biologically Plausible Object Recognition Strategies.- Structured Kalman Filter for Tracking Partially Occluded Moving Objects.- Face Recognition under Varying Views.- Time Delay Effects on Dynamic Patterns in a Coupled Neural Model.- Pose-Independent Object Representation by 2-D Views.- An Image Enhancement Technique Based on Wavelets.- Front-End Vision: A Multiscale Geometry Engine.- Face Reconstruction Using a Small Set of Feature Points.- Modeling Character Superiority Effect in Korean Characters by Using IAM.- Wavelet-Based Stereo Vision.- A Neural Network Model for Long-Range Contour Diffusion by Visual Cortex.- Automatic Generation of Photo-Realistic Mosaic Image.- The Effect of Color Differences on the Detection of the Target in Visual Search.- A Color-Triangle-Based Approach to the Detection of Human Face.- Multiple People Tracking Using an Appearance Model Based on Temporal Color.- Face and Facial Landmarks Location Based on Log-Polar Mapping.- Biology-Inspired Early Vision System for a Spike Processing Neurocomputer.- A New Line Segment Grouping Method for Finding Globally Optimal Line Segments.- A Biologically-Motivated Approach to Image Representation and Its Application to Neuromorphology.- A Fast Circular Edge Detector for the Iris Region Segmentation.- Face Recognition Using Foveal Vision.- Fast Distance Computation with a Stereo Head-Eye System.- Bio-inspired Texture Segmentation Architectures.- 3D Facial Feature Extraction and Global Motion Recovery Using Multi-modal Information.- Evaluation of Adaptive NN-RBF Classifier Using Gaussian Mixture Density Estimates.- Scene Segmentation by Chaotic Synchronization and Desynchronization.- Electronic Circuit Model of Color Sensitive Retinal Cell Network.- The Role of Natural Image Statistics in Biological Motion Estimation.- Enhanced Fisherfaces for Robust Face Recognition.- Invited Paper (6).- A Humanoid Vision System for Versatile Interaction.- ICA and Space-Variant Imaging.- The Spectral Independent Components of Natural Scenes.- Topographic ICA as a Model of Natural Image Statistics.- Independent Component Analysis of Face Images.- Orientation Contrast Detection in Space-Variant Images.- Multiple Object Tracking in Multiresolution Image Sequences.- A Geometric Model for Cortical Magnification.- Neural Networks and Applications.- Tangent Fields from Population Coding.- Efficient Search Technique for Hand Gesture Tracking in Three Dimensions.- Robust, Real-Time Motion Estimation from Long Image Sequences Using Kalman Filtering.- T-CombNET - A Neural Network Dedicated to Hand Gesture Recognition.- Invited Paper (7).- Active and Adaptive Vision: Neural Network Models.- Invited Paper (8).- Temporal Structure in the Input to Vision Can Promote Spatial Grouping.
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