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Visual Object Recognition and Detection, 6 credits
Visuell detektion och igenkänning, 6 hp
TSBB17
Main field of study
Computer Science and EngineeringCourse level
Second cycleCourse type
Programme courseExaminer
Fahad KhanDirector of studies or equivalent
Klas NordbergEducation components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
ECV = Elective / Compulsory / Voluntary
Main field of study
Computer Science and EngineeringCourse level
Second cycleAdvancement level
A1XCourse offered for
- Computer Science and Engineering, M Sc in Engineering
- Information Technology, M Sc in Engineering
- Computer Science and Software Engineering, M Sc in Engineering
- Applied Physics and Electrical Engineering, M Sc in Engineering
- Applied Physics and Electrical Engineering - International, M Sc in Engineering
Entry requirements
Note: Admission requirements for non-programme students usually also include admission requirements for the programme and threshold requirements for progression within the programme, or corresponding.
Prerequisites
Basic image processing: thresholding, segmentation, edge detection from for example Signals, Information and Images or Digital Image Processing. Use of Matlab. Probability Theory and Statistics.
Intended learning outcomes
After the course the students should be able to:
- identify basic terminologies, theories and methods for recognition and detection of objects in images
- understand current approaches for object recognition and detection, to actively analyse their strengths and weaknesses
- develop, experimentally evaluate different recognition/detection algorithms and summarize the results
- select appropriate methods for automatic training of recognition and detection systems
- understand basic theories of how the brain processes visual information to perform object recognition and detection tasks
Course content
Invariant local features and feature extraction in digital images, bag-of-features framework, principles of object recognition and detection, local spatial constraints, introduction to convolutional neural networks, support vector machines learning, shape descriptors and matching, part-based models for recognition, the role of context in recognition, overview of object recognition in biological systems and deep features.
Teaching and working methods
The course consists of two parts that are presented in parallel. One part is more theoretical and is based on a larger number of lectures that present and illustrate basic methods for object recognition and detection. This part concludes with a written examination. The other part is more practical and begins with an introduction to two projects: one in the area of object recognition and the other in the area of object detection. The course participants are divided into small groups, and each group carries out both these applied projects, which shall demonstrate a number of methods presented in the theoretical part of the course. The results from each project group are presented orally at seminars and are documented in reports. Guidance for the projects is only given during the course semester. Each project is concluded by an analysis and reflection of the project work.
Examination
| PRA1 | Oral and written presentation of project assignment | 3 credits | U, G |
| TEN1 | Written examination | 3 credits | U, 3, 4, 5 |
Grades
Four-grade scale, LiU, U, 3, 4, 5Course literature
There is no required textbook for the course. Material will be handed out or made available on the course web page. We will obtain most of our content from the papers we read. Further, Steve Palmer's Vision Science, Richard Szeliski's Computer Vision: Algorithms and Applications, and Forsyth and Ponce's Computer vision: A Modern Approach have useful source material.
Department
Institutionen för systemteknikDirector of Studies or equivalent
Klas NordbergExaminer
Fahad KhanEducation components
Preliminary scheduled hours: 48 hRecommended self-study hours: 112 h
| Code | Name | Scope | Grading scale |
|---|---|---|---|
| PRA1 | Oral and written presentation of project assignment | 3 credits | U, G |
| TEN1 | Written examination | 3 credits | U, 3, 4, 5 |
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at http://styrdokument.liu.se/Regelsamling/Innehall/Utbildning_pa_grund-_och_avancerad_niva.
Course literature is preliminary.
There is no course literature available for this course in studieinfo.
Note: The course matrix might contain more information in Swedish.
I = Introduce, U = Teach, A = Utilize
| I | U | A | Modules | Comment | ||
|---|---|---|---|---|---|---|
| 1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
| 1.1 Knowledge of underlying mathematics and science (G1X level) |
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| 1.2 Fundamental engineering knowledge (G1X level) |
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| 1.3 Further knowledge, methods, and tools in one or several subjects in engineering or natural science (G2X level) |
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| 1.4 Advanced knowledge, methods, and tools in one or several subjects in engineering or natural sciences (A1X level) |
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| 1.5 Insight into current research and development work |
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| 2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
| 2.1 Analytical reasoning and problem solving |
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| 2.2 Experimentation, investigation, and knowledge discovery |
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| 2.3 System thinking |
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| 2.4 Attitudes, thought, and learning |
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| 2.5 Ethics, equity, and other responsibilities |
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| 3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
| 3.1 Teamwork |
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| 3.2 Communications |
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| 3.3 Communication in foreign languages |
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| 4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
| 4.1 External, societal, and environmental context |
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| 4.2 Enterprise and business context |
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| 4.3 Conceiving, system engineering and management |
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| 4.4 Designing |
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| 4.5 Implementing |
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| 4.6 Operating |
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| 5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
| 5.1 Societal conditions, including economic, social, and ecological aspects of sustainable development for knowledge development |
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| 5.2 Economic conditions for knowledge development |
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| 5.3 Identification of needs, structuring and planning of research or development projects |
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| 5.4 Execution of research or development projects |
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| 5.5 Presentation and evaluation of research or development projects |
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