Human action recognition

Code:

MVCOMP15

Acronym:

RAH

Keywords
Classification	Keyword
CNAEF	Engineering and related techniques

Instance: 2024/2025 - 4T

Active?	Yes
Responsible unit:	Department of Electrical and Computer Engineering
Course/CS Responsible:	Master in Computer Vision

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MVCOMP	1	Syllabus	1	-	3	21	81

Teaching language

English
Obs.: Lecionada por docentes da Universidade da Corunha

Objectives

The major goal in this area of computer vision is to build systems that can automatically find human figures in either images or video sequences and determine what action they are performing. The recognition of human figures and actions is an important problem, with many practical applications. This technology is directly applicable to human-computer interaction, image and video retrieval and search, security and surveillance, video motion capture and automated vehicle driver assistance systems.

Learning outcomes and competences

Students should acquire the knowledge visual recognition techniques applied to the recognition of people and body parts; should be able to conduct the analysis and evaluation of human recognition applications; should be able to develop tools based on advanced technologies for the recognition of human actions.

Working method

À distância

Program

Detection an d tracking of people.
Detection and monitoring of faces , extremities, and other features of interest.
Recognition of postural and behavioral patterns.
Applications of the recognition of human actions.

Mandatory literature

I.-O. Stathopoulou, G.A. Tsihrintzis; Visual Affect Recognition, IOS Press, 2010

Teaching methods and learning activities

Participatory lectures, learning based on the resolution of practical cases, practical work and autonomous study by the students. The virtual classroom will be intensively used.

Evaluation Type

Distributed evaluation with final exam

Assessment Components

Designation	Weight (%)
Exame	33,30
Trabalho prático ou de projeto	66,70
Total:	100,00

Amount of time allocated to each course unit

Designation	Time (hours)
Apresentação/discussão de um trabalho científico	10,00
Elaboração de projeto	30,00
Estudo autónomo	20,00
Frequência das aulas	21,00
Total:	81,00

Eligibility for exams

To be defined in each curricular year.

Calculation formula of final grade

Two practical projects and one written exam. The final cla ssification is the arithmetic average of the three individual classifications.