| Study programme competencies |
| Code | Study programme competences |
| A23 | CE23 - Coñecemento e capacidade de aplicación dos conceptos, metodoloxías e tecnoloxías de procesado de audio, imaxe e vídeo en diferentes formatos. |
| B2 | CB2 - Que os estudantes saiban aplicar os seus coñecementos ao seu traballo ou vocación dunha forma profesional e posúan as competencias que adoitan demostrarse por medio da elaboración e defensa de argumentos e a resolución de problemas dentro da súa área de estudo |
| B3 | CB3 - Que os estudantes teñan a capacidade de reunir e interpretar datos relevantes (normalmente dentro da súa área de estudo) para emitir xuízos que inclúan unha reflexión sobre temas relevantes de índole social, científica ou ética |
| B4 | CB4 - Que os estudantes poidan transmitir información, ideas, problemas e solucións a un público tanto especializado como non especializado |
| B7 | CG2 - Elaborar adecuadamente e con certa orixinalidade composicións escritas ou argumentos motivados, redactar plans, proxectos de traballo, artigos científicos e formular hipóteses razoables. |
| B8 | CG3 - Ser capaz de manter e estender formulacións teóricas fundadas para permitir a introdución e explotación de tecnoloxías novas e avanzadas no campo. |
| B9 | CG4 - Capacidade para abordar con éxito todas as etapas dun proxecto de datos: exploración previa dos datos, preprocesado, análise, visualización e comunicación de resultados. |
| B10 | CG5 - Ser capaz de traballar en equipo, especialmente de carácter multidisciplinar, e ser hábiles na xestión do tempo, persoas e toma de decisións. |
| C1 | CT1 - Utilizar as ferramentas básicas das tecnoloxías da información e as comunicacións (TIC) necesarias para o exercicio da súa profesión e para a aprendizaxe ao longo da súa vida. |
| C4 | CT4 - Valorar a importancia que ten a investigación, a innovación e o desenvolvemento tecnolóxico no avance socioeconómico e cultural da sociedade. |
| Learning aims | |||
| Learning outcomes | Study programme competences | ||
| To understand the basic concepts and techniques of image, video and digital audio processing and analysis. To know how to evaluate the adequacy of the methodologies applied in specific audiovisual processing problems. To know how to describe an image signal, at a content level, by its different characteristics. To apply different basic techniques to computer vision problems. | A23 |
B2 B3 B4 B7 B8 B9 B10 |
C1 C4 |
| Contents |
| Topic | Sub-topic |
| 1. Introduction to the representation of visual information. Preprocessing |
The digital image and its properties Image digitalization Properties, metrics and topology Statistical properties, histogram Gray level transformations Geometric transformations Interpolation |
| Fundamentals of visual information processing. | Spatial filters: Convolution Frequency filters: Fourier Applications: Noise, Enhancement, Smoothing Morphological Operators Edge Operators |
| Image Modeling and Analysis | Keypoints (Corners, Singular Points) Shape Descriptors Contours Representations Texture |
| Fundamentals of Segmentation and Pattern Recognition | Thresholding Region-based segmentation AI-based segmentation (Clustering, ...etc) Hough Transform Deformable models. Segmentation Evaluation Pattern Recognition and Image Classification |
| Fundamentals of Dynamic Vision | Motion Detection and Characterization Optical Flow Tracking |
| Fundamentos de Procesado y represantación de información sonora | Descriptores Temporales Descriptores Espectrales Descriptores cepstrales |
| Planning | ||||
| Methodologies / tests | Competencies | Ordinary class hours | Student’s personal work hours | Total hours |
| Laboratory practice | A23 B2 B3 B4 B8 B9 B10 C4 C1 | 10 | 30 | 40 |
| Research (Research project) | A23 B2 B3 B4 B7 B8 B9 B10 C1 C4 | 10 | 50 | 60 |
| Workbook | B8 B9 B10 C4 | 6 | 12 | 18 |
| Mixed objective/subjective test | B9 B10 C1 | 1 | 1 | 2 |
| Guest lecture / keynote speech | A23 B2 B3 B4 B9 B10 C1 C4 | 15 | 15 | 30 |
| Personalized attention | 0 | 0 | 0 | |
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | ||||
| Methodologies |
| Methodologies | Description |
| Laboratory practice | Activity that allows students to learn effectively through hands-on activities such as demonstrations, exercises, or simulations |
| Research (Research project) | Activity that allows students to study and learn the application and combination of the different techniques studied to solve problems based on real application areas. |
| Workbook | Set of texts and written documentation, mainly in foreign language (English), which were compiled and edited as a source of information and deepening in the contents worked in the master classes. |
| Mixed objective/subjective test | Activity for the evaluation of the comprehension and analytical capacity of the techniques used by the student to solve certain problems. |
| Guest lecture / keynote speech | Oral exposition complemented with the use of audiovisual media and the introduction of some questions addressed to the students, with the aim of transmitting knowledge as well as stimulating the critical reasoning of the students. |
| Personalized attention |
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| Assessment | |||
| Methodologies | Competencies | Description | Qualification |
| Workbook | B8 B9 B10 C4 | Oral presentation of a work analyzed and prepared in group. | 10 |
| Mixed objective/subjective test | B9 B10 C1 | Objective test with different assumptions and questions that will evaluate the student's capacity of understanding, reasoning and knowledge of the subject. | 40 |
| Research (Research project) | A23 B2 B3 B4 B7 B8 B9 B10 C1 C4 | Completion of the work of study, implementation and combination of computer vision techniques. | 30 |
| Laboratory practice | A23 B2 B3 B4 B8 B9 B10 C4 C1 | Compulsory attendance and completion of the lab practices. Understanding and critical analysis of each one of them. | 20 |
| Assessment comments | |||
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In each of the following parts it will be mandatory to achieve a minimum grade in order to pass the subject:
If a student presents any of the assignments subject to assessment, he/she will be considered PRESENTED and, therefore, if he/she does not attend any of the other parts, the final grade will be a FAIL MARK. Students enrolled on a part-time basis may be given facilities, prior communication with the professor in charge. |
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| Sources of information |
| Basic |
Andrew Blake (1998). Active Contours . Springer
Anil Jain (1989). Fundamentals of Digital Image Processing. Prentice Hall
Milan Sonka (1999). Image Processing, Analysis and Machine Vision. PWS
Rafael González (1996). Tratamiento Digital de Imágenes. Addison-Wesley |
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| Complementary | |
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| Recommendations | |
| Subjects that it is recommended to have taken before |
| Subjects that are recommended to be taken simultaneously |
| Subjects that continue the syllabus |
| Other comments | |