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image processing
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Multiple View Geometry in the Space-Time
Multiple View Geometry for Non-rigid Motions Viewed from Translational Cameras
Multiple Similarities Based Kernel Subspace Learning for Image Classification
Multiple Range Image Registration by Matching Local Log-Polar Range Images
Multiple-Person Tracking Using a Plan-View Map with Error Estimation
Multiperspective Distortion Correction Using Collineations
Multiclass Image Labeling with Semidefinite Programming
Multi-camera Tracking of Articulated Human Motion Using Motion and Shape Cues
Multi-camera People Tracking by Collaborative Particle Filters and Principal Axis-Based Integration
Motion Observability Analysis of the Simplified Color Correlogram for Visual Tracking
Motion Guided Video Sequence Synchronization
Motion Detection in Driving Environment Using U-V-Disparity
Monocular Tracking of 3D Human Motion with a Coordinated Mixture of Factor Analyzers
Molding Face Shapes by Example
Modelling the Effect of View Angle Variation on Appearance-Based Gait Recognition
Modeling 3D Objects from Stereo Views and Recognizing Them in Photographs
Mirror Localization for Catadioptric Imaging System by Observing Parallel Light Pairs
Minimal Weighted Local Variance as Edge Detector for Active Contour Models
Microscopic Surface Shape Estimation of a Transparent Plate Using a Complex Image
Measurement of Reflection Properties in Ancient Japanese Drawing Ukiyo-e
Maximally Stable Local Description for Scale Selection
Matching Gait Image Sequences in the Frequency Domain for Tracking People at a Distance
Markov Random Field Modeled Level Sets Method for Object Tracking with Moving Cameras
Markovian Framework for Foreground-Background-Shadow Separation of Real World Video Scenes
MAPACo-Training: A Novel Online Learning Algorithm of Behavior Models
Machine Vision in Early Days: Japan’s Pioneering Contributions
Machine Learning for High-Speed Corner Detection
Logical DP Matching for Detecting Similar Subsequence
Located Hidden Random Fields: Learning Discriminative Parts for Object Detection
Localized Content-Based Image Retrieval Using Semi-Supervised Multiple Instance Learning
Less Is More: Coded Computational Photography
Learning to Detect Objects of Many Classes Using Binary Classifiers
Learning to Combine Bottom-Up and Top-Down Segmentation
Learning Semantic Scene Models by Trajectory Analysis
Learning Parameter Tuning for Object Extraction
Learning Nonlinear Manifolds from Time Series
Learning Multi-category Classification in Bayesian Framework
Learning Generative Models for Monocular Body Pose Estimation
Learning Gabor Magnitude Features for Palmprint Recognition
Learning Effective Intrinsic Features to Boost 3D-Based Face Recognition
Learning Discriminative Canonical Correlations for Object Recognition with Image Sets
Learning Compositional Categorization Models
Learning and Incorporating Top-Down Cues in Image Segmentation
Learning a Fast Emulator of a Binary Decision Process
Learning 2D Hand Shapes Using the Topology Preservation Model GNG