Journal Information
Image and Vision Computing (IVC)
Impact Factor:
Call For Papers
Image and Vision Computing has as a primary aim the provision of an effective medium of interchange for the results of high quality theoretical and applied research fundamental to all aspects of image interpretation and computer vision. The journal publishes work that proposes new image interpretation and computer vision methodology or addresses the application of such methods to real world scenes. It seeks to strengthen a deeper understanding in the discipline by encouraging the quantitative comparison and performance evaluation of the proposed methodology. The coverage includes: image interpretation, scene modelling, object recognition and tracking, shape analysis, monitoring and surveillance, active vision and robotic systems, SLAM, biologically-inspired computer vision, motion analysis, stereo vision, document image understanding, character and handwritten text recognition, face and gesture recognition, biometrics, vision-based human-computer interaction, human activity and behavior understanding, data fusion from multiple sensor inputs, image databases.

In addition to regular manuscripts, Image and Vision Computing Journal solicits manuscripts for the Opinions Column, aimed at initiating a free forum for vision researchers to express their opinions on past, current, or future successes and challenges in research and the community.

An opinion paper should be succinct and focused on a particular topic. Addressing multiple related topics is also possible if this helps making the point. While posing questions helps raising awareness about certain issues, ideally, an opinion paper should also suggest a concrete direction how to address the issues. Topics of interest include, but are not limited to:

    Comments on success and challenges in a (sub-) field of computer vision,
    Remarks on new frontiers in computer vision
    Observations on current practices and trends in research, and suggestions for overcoming unsatisfying aspects
    Observations on current practices and trends in the community regarding, e.g., reviewing process, organizing conferences, how journals are run, and suggestions for overcoming unsatisfying aspects
    Reviews of early seminal work that may have fallen out of fashion
    Summaries of the evolution of one's line of research
    Recommendations for educating new generations of vision researchers.
Last updated by Dou Sun in 2021-03-20
Special Issues
Special Issue on Video Computation and Reconstruction in Digital Twins
Submission Date: 2022-02-20

The topics may include but are not limited to: - Data Security of Digital Twins in Video Reconstruction - Modeling and Calculation of Digital Twins in Video Reconstruction - Multi-scale Fusion Modeling of Digital Twins in Video Reconstruction - Physical Vision System of Digital Twins in Video Reconstruction - Design of Digital Twins System Cluster in Video Reconstruction - Model Authentication and Continuous Guarantee Method of Digital Twins - Data-Driven and Physical Model Fusion State Evaluation - Scene Data Acquisition and Transmission Based on Video Computing - Digital Twins Complex Virtual Reality System Based on Video Computing - VR Effect of Digital Twin Technology on Video Reconstruction - High-Performance Computing for Complex Functions of Digital Twins System - Diversified Application Scenarios of Digital Twins System
Last updated by Dou Sun in 2021-07-25
Special Issue on Development of a real-time violence detection framework through Big Data Analysis and Deep Reinforcement Learning
Submission Date: 2022-04-25

Potential topic of interest include but not limited to: - Techniques to improve the SVAS method to deal with moving cameras and multi-camera data set. - Selective ID protection for intelligent video surveillance systems. - Gaussian Mixture Model (GMM) for background modelling in intelligent video surveillance systems. - Development of a real-time violence detection framework through Big Data Analysis and Deep Reinforcement Learning. - Methods to improve the security management process in intelligent video surveillance systems. - Feasibility study on the implementation of data-driven intelligence for video surveillance systems. - Spatio-temporal texture modelling for real-time crowd anomaly detection. - Techniques to overcome close proximity and irregular motion pattern in crowd analysis for intelligent video surveillance.
Last updated by Dou Sun in 2021-12-20
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