COMP53415: Computer Vision

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• To develop students knowledge of key concepts, approaches and algorithms in Computer Vision related to automatic understanding of image and video data.
• To develop students critical understanding and appreciation of current theoretical and empirical research in computer vision and its application within industry.

• Content will cover classical and deep learning approaches to Computer Vision and be chosen from:
• Comprehensive image feature representations
• Object detection, object classification and scene understanding
• Segmentation, superpixels, saliency, optical flow and image registration
• Stereo vision and reconstruction from multiple images
• Object tracking and behaviour analysis
• Real-time processing approaches and trade-offs
• Image transformation and augmentation
• Applications of computer vision

Subject-specific Knowledge:

• By the end of this module, students should be able to demonstrate:
• a critical understanding of the contemporary computer vision topics presented, how these are applicable to relevant industrial problems and have future potential for emerging needs in both a research and industrial setting.
• knowledge of state-of-the-art deep learning models for computer vision tasks.
• advanced knowledge of the principles and practice of analysing computer vision algorithms to determine problem suitability.
• an understanding of managing the trade-off between task performance and real-time processing performance within the context of computer vision.
• an understanding of the most recent advancements in the relevant academic literature and their implications for current industry practice.

Subject-specific Skills:

• By the end of this module, students should have developed highly specialised and advanced technical, professional and academic skills that enable them to:
• formulate and solve problems that involve the automatic understanding of image and video data sources using a range of algorithmic approaches.
• develop computer vision software solutions and use appropriate algorithms and approaches to address both industrial and research application tasks.

Key Skills:

• Written communication.
• Planning, organising and time management.
• Problem solving and analysis.
• Using initiative.
• Adaptability.
• Numeracy.
• Computer Literacy.

• A combination of lectures, computer classes, and guided reading will contribute to achieving the aims and learning outcomes of this module.
• The summative assessment will test students knowledge and critical understanding of the material covered in the module and their analytical and problem-solving skills.
• The assignment element of the coursework component consists of a coding exercise with accompanying report.

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