Visual Object Tracking: Challenges and Applications

Dear Colleagues,

Visual tracking aims to locate the target specified in the initial frame, which has many realistic applications such as video surveillance, augment reality, and behavior analysis. In spite of numerous efforts, this is still a challenging task due to factors such as deformation, illumination change, rotation, and occlusion, to name a few. This Topic promotes scientific dialogue for the added value of novel methodological approaches and research in the specified areas. Our interest is in the entire end-to-end spectrum of visual object tracking research, from motion estimation, appearance representation, strategic frameworks, models, and best practices to sophisticated research related to radical innovation. The topics of interest include but are not limited to the following indicative list:

• Enabling Technologies for visual object tracking research:
• Machine learning;
• Neural networks;
• Image processing;
• Bot technology;
• AI agents;
• Reinforcement learning;
• Edge computing;

• Methodologies, frameworks, and models for artificial intelligence and visual object tracking research:
• For innovations in business, research, academia industry, and technology;
• For theoretical foundations and contributions to the body of knowledge of visual object tracking;

• Best practices and use cases;
• Outcomes of R&D projects;
• Industry-government collaboration;
• Security and privacy issues;
• Ethics on visual object tracking and AI;
• Social impact of AI.

Dr. Shunli Zhang
Dr. Xin Yu
Prof. Dr. Kaihua Zhang
Dr. Yang Yang
Topic Editors