EL3105 Eng Electronic Engineering

Academic Year: 2024-2025 Assessment Introduction: Course: BEng Electronic EngineeringBEng Robotic EngineeringMEng Robotic EngineeringModule Code: EL3105

Module Title: Computer Vision Title of the Brief: Video Stabilisation

Type of assessment: Assignment

Introduction

This Assessment Pack consists of a detailed assignment brief, guidance on what you need toprepare, and information on how class sessions support your ability to complete successfully.The tutor responsible for this coursework will be available on 28th of January 2025 to answer

questions related to this assessment. You’ll also find information on this page to guide you on

how, where, and when to submit. If you need additional support, please make a note of theservices detailed in this document.

Submission details; How, when, and where to submit:

Assessment Release date: 21/01/2025.Assessment Deadline Date and time: 28/03/2024 (23:59).Please note that this is the final time you can submit – not the time to submit!You should aim tosubmit your assessment in advance of the deadline.The Turnitin submission link on Blackboard, will be visible to you on: 03/03/2025.

Feedback will be provided by: 06/05/2025.This assignment constitutes 50% of the total module assessment mark. You should write a

report for this assignment documenting your solutions for the tasks defined in the assignmentbrief given below. The report should include a very short introduction describing the problem,

description of your adopted solutions, a more extensive description of the results and

conclusions section summarising the results. The report should be approximately 1500 wordslong, plus relevant materials (References and Appendices). Youshould use Harvardreferencing system for this report. The report should be submitted electronically to “Video Stabilisation” Turnitin through Blackboard.You should submit a documented matlab/python code solving the given tasks. The codeshould be self-contained, i.e., it should be able to run as it is, without a need for any

additional tools/libraries. In case, there are multiple files please create a single zip codeDisclaimer: The information provided in this assessment brief is correct at time of publication. In the unlikely event that any changes

are deemed necessary, they will be communicated clearly via e-mail and a new version of this assessment brief will be circulated.archive containing all the files. The code should be submitted separately from th代写EL3105 Eng Electronic Engineeringe report intoBlackboard EL3105 assignment area denoted as “Video Stabilisation Code”. Note: If you have any valid mitigating circumstances that mean you cannot meet anassessment submission deadline and you wish to request an extension, you will need to applyonline, via MyUCLan with your evidence prior to the deadline. Further information onMitigating Circumstances via this link.We wish you all success in completing your assessment. Read this guidance carefully, andany questions, please discuss with your Module Leader.Teaching into assessment

The tutor responsible for this coursework will be available on 28/01/2025 between 14:00 inthe 16:00 to answer questions related to this assessment.All thealgorithmic aspects necessary for the successful completion of the assignment havebeencovered during the lectures, tutorial, and laboratory sessions, these include featuredetection, descriptor calculation, robust matching, estimation of a transformation aligningmatched features, tracking and image warping.

Additional Support

All links are available through the online Student Hub

1. Our Library resources link can be found in the library area of the Student Hub or viaour subject librarian at SubjectLibrarians@uclan.ac.uk. (Mr. Neil MarshallNMarshall7@uclan.ac.uk)

2. Support with your academic skills development (academic writing, critical thinking anreferencing) is available through WISER on the Study Skills section of the Student Hub.

3. For help with Turnitin, see Blackboard and Turnitin Support on the Student Hub
4. If you have a disability, specific learning difficulty, long-term health or mental healthcondition, and not yet advised us, or would like to review your support, Inclusive Support can assist with reasonable adjustments and support. To find out more, you

can visit the Inclusive Support page of the Student Hub.

5. For mental health and wellbeing support, please complete our online referral form, oremail wellbeing@uclan.ac.uk. You can also call 01772 893020, attend a drop-in, or visitour UCLan Wellbeing Service Student Hub pages for more information.

6. For any other support query, please contact Student Support viastudentsupport@uclan.ac.uk.

For consideration of Academic Integrity, please refer to detailed guidelines in our policydocument . All assessed work should be genuinely your own work, and all resources

fully cited.8. For this assignment, you are not permitted to use any category of AI tools.Assignment Brief

This assignment is designed to give you an insight into selected aspects of computer vision

applied to image feature extraction, feature matching, and motion compensation. You are

asked to solve various tasks including detection of image features and their robust matching,write computer vision software as well as test your solution and interpret the results.This assignment will enable you to:Deepen your understanding of the features/keypoints detection and robust matchingbetween features, image transformation and warping models.Recognise software design challenges behind implementations of computer vision

algorithms.Design and optimise software to meet specified requirements.Acquire a hands-on understanding of image-based camera motion compensation.

(These correspond to point 1, 2, 4 and 5 of the module’s learning outcomes. Module learning

outcomes are provided in the Module Descriptor)

The assignment consists of two main tasks. The first task is to explain and justify your

selected methodology for video stabilisation, specifically focusing on camera motion jittercompensation. This should include a discussion of jitter compensation for a moving camera,

handling moving objects within the scene, depth of field, and the ability to operate in realtime.The second task is to implement the selected method usingMATLAB and/or Python. You areprovided with two pre-recorded videos that increase in scene complexity. The first video

features a static scene with a jittering, but otherwise static, camera. The second videocontains a scene with moving objects. The two videos, video_seq_1.avi andvideo_seq_2.avi, are available on the Computer Vision Blackboard site.

You are expected to write a MATLAB (and/or Python) program that removes the apparent

scene motion caused by the camera jitter in the video sequences. Your algorithm should be

designed to process the images sequentially, meaning that when estimating the currentimage correction, it should only use the current and preceding frames. Additionally, thealgorithm should be optimized to work in real-time, with computational complexity that doesnot depend on the length of the sequence.Late work If the report and/or code are submitted after the deadline they will be automatically flaggedas late. Except where an extension of the hand-in deadline date has been approved latenesspenalties will be applied in accordance with the University policies.

Marking scheme Your report should contain the following elements; it will be marked in accordance with thefollowing marking scheme:

Item Weight (%) ustification of the adopted video stabilisation approach30

2. Software implementation4Evaluation of the results15

4. Presentation of the repor1

European Conference on Computer VisionFeedback Guidance:

Reflecting on Feedback: how to improve.

From the feedback you receive, you should understand: The grade you achieved. The best features of your work.

What you can do to improve in the future - feedforward.Use the WISER: Academic Skills Development service. WISER can reviewfeedback and help you understand your feedback. You can also use theWISER Feedback GlossaryNext Steps:

List the steps have you taken to respond to previous feedback.Summarise your achievementsEvaluate where you need to improve here (keep handy for futurework):