2021 The 14th International Conference on Machine Vision (ICMV 2021)

The emergence of Machine Vision as a ubiquitous platform for innovations has laid the foundation for the rapid growth of the Information. Side-by-side, the use of mobile and wireless devices such as PDA, laptop, and cell phones for accessing the Internet has paved the ways for related technologies to flourish through recent developments. In addition, the Machine Vision Technology is promoting better integration of the digital world with physical environment. This conference serves to foster communication among researchers and practitioners working in a wide variety of scientific areas with a common interest in improving Machine Vision related techniques. 

High quality, original papers are solicited in all areas of Machine Vision. The final program will be the result of a highly selective review process designed to include the best work of its kind in every category. The program will include invited talks as well as oral and poster presentations of refereed papers.

Topics of interest for submission include, but are not limited to:

Submission Session on Easychair Submission System:

SPECIAL SESSION I: Camera Based and Mobile Recognition
SPECIAL SESSION II: Advanced Imaging and Tomography
SPECIAL SESSION III: Machine Vision for Autonomous Driven Cars under Harsh Environmental Conditions

Machine Vision, Image Processing, and Pattern Analysis

Imaging Sensors
Color and Texture Analysis
Segmentation
Motion and Tracking
Stereo Vision
Biometrics Recognition
Image-Based Modeling
Calibration and Geometry
Illumination and Reflectance Modeling
Soft Computing for Machine Vision
Physics-Based Modeling
Artificial Intelligence for Machine Vision
Video Analysis
Face and Gesture Recognition
Action and Event Recognition
Similarity/Dissimilarity Metrics
Machine Learning
Performance Evaluation
Medical Image Analysis
Image and Video Retrieval
Structure from Motion
Image Registration
Image Enhancement
Clustering
Morphology and Blob Analysis
Applications of Machine Vision

Computer Vision and Image Analysis

Active Vision
Early Vision
Feature Extraction
Motion Analysis
Representation
Recognition (2D and 3D)
Texture and Colour
Scene Understanding
Segmentation
Shape from X
Visual Navigation

Pattern Recognition and Basic Technologies

Statistical Pattern Recognition
Structural and Syntactic Pattern Recognition
Neural Networks
Machine Learning and Data Mining
Artificial Intelligence and Symbolic Learning
Classification and Clustering
Feature Selection, Dimensionality Reduction, Manifold Learning
Kernel Methods and Support Vector Machines
Invariance in Recognition
Multiresolution Techniques
OCR, Document Analysis and Understanding
Information Retrieval