Deep Learning for Object Detection and Tracking in Video Surveillance Applications
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Robotics and Automation".
Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 4934
Special Issue Editors
Interests: computer vision and pattern recognition; cybersecurity; intelligent systems; bio-inspired computation; multimodal machine learning
Interests: computer vision; image processing; deep learning
Interests: computer vision; deep learning; intelligent transportation; cyber-physical systems security; adversarial machine learning
Special Issue Information
Dear Colleagues,
We are pleased to announce the launch of a new Special Issue on “Deep Learning for Object Detection and Tracking in Video Surveillance Applications”, to be published in the Applied Sciences journal (https://www.mdpi.com/journal/applsci).
With the ubiquitous availability of video cameras and advances in deep learning, the past few years have witnessed an immensely growing interest in intelligent video analytics from both academia and industry. The goal is to automatically analyze video content, detect objects, and track their temporal and spatial changes under challenging scenarios. This can provide invaluable higher-level insights that can benefit decision making and improve safety. We encourage submissions of original work related to utilizing deep learning approaches to provide end-to-end applications for object detection and tracking in videos or live streams. There is a wide range of potential indoor and outdoor video surveillance applications in business, industry, smart cities, and critical infrastructures, such as detecting and tracking vehicles and pedestrians for smart transportation, monitoring traffic jams and accidents, vehicle counting in smart parking spaces, detecting adversarial activities to ensure safety, monitoring people with health issues, analyzing facial expressions and detecting humans’ mood and emotional state, tracking eye and lip movements, recognizing human gestures, analyzing gait and recognizing walking persons, managing crowded areas and counting entrances and exits, tracking customers’ behavior and spotting shoplifters, analyzing games and forecasting winners, reidentifying people, improving recognition in the presence of occlusion, etc.
Topics of interest are related to deep learning approaches for object detection and tracking in various application domains, including but not limited to:
- Smart cities;
- Smart homes;
- Smart healthcare;
- Autonomous vehicles and smart parking systems;
- Visual homeland security and surveillance;
- Crowd management;
- Human behavior, gesture, and sign language;
- Human motion analysis and recognition;
- Vision-based human–computer interaction;
- Cognitive robots and navigation systems;
- Safety and adversarial activity recognition;
- Person tracking in retail stores;
- Adversarial attacks against DL-based object detection and/or tracking;
- Drone-based surveillance and monitoring;
- Multi-modal fusion of video and other sensory data for surveillance;
- Anomalous activities/events detection and tracking;
- Edge-assisted DL-based visual surveillance.
All submissions will be subject to a peer reviewing process on the basis of relevance, significance, and technical and presentation quality, by at least two independent reviewers. Authors must conform to the guidelines available on the journal website.
Prof. Dr. El-Sayed El-Alfy
Dr. Motaz Alfarraj
Dr. Abdul Jabbar Siddiqui
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- deep learning
- object detection
- object tracking
- activity recognition
- gesture and sign language
- gait analysis and recognition
- lip reader
- video analytics
- video surveillance
- crowd management
- smart transportation
- smart parking
- smart cities
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