Activity Recognition

Activity recognition has become a very active area in the past few years. It is a challenging problem that has attracted the attention of the research community due to its practical and real-world applications, such as human computer interfaces, content based video indexing, video surveillance and robotics, among others. A definition for such task can be described as labeling video segments containing human motion with activity classes. For instance, we can define an activity as a composition of one or more actions organized temporally.

Basically, the literature divides the activity recognition task on three main steps: (i) data representation (feature extraction), allowing the image/video content to be represented in a more discriminative space rich enough to allow a proper recognition; (ii) activity segmentation, producing atomic movements by identifying suitable break points resulting into segments. These segments could be used to describe the action as a whole or even the task to find the spatial and temporal location of the action; and (iii)  activity classification, which the purpose is to learn a function that can assign (discrete) labels to the images/videos.


Related Publications

Carlos Antônio Caetano Júnior

Motion-Based Representations for Activity Recognition PhD Thesis

Universidade Federal of Minas Gerais, 2020.

Abstract | BibTeX

Victor Hugo Cunha de Melo; Jesimon Barreto Santos; Carlos Antonio Caetano Junior; Jessica Sena; Otavio A B Penatti; William Robson Schwartz

Object-based Temporal Segment Relational Network for Activity Recognition Inproceedings

In: Conference on Graphic, Patterns and Images (SIBGRAPI), pp. 1-8, 2018.


Carlos Antonio Caetano Junior; Jefersson A dos Santos; William Robson Schwartz

Statistical Measures from Co-occurrence of Codewords for Action Recognition Inproceedings

In: VISAPP 2018 - International Conference on Computer Vision Theory and Applications, pp. 1-8, 2018.

Links | BibTeX

Igor Leonardo Oliveira Bastos; Larissa Rocha Soares; William Robson Schwartz

Pyramidal Zernike Over Time: A spatiotemporal feature descriptor based on Zernike Moments Inproceedings

In: Iberoamerican Congress on Pattern Recognition (CIARP 2017), pp. 77-85, 2017.

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Carlos Antonio Caetano Junior; Victor Hugo Cunha de Melo; Jefersson Alex dos Santos; William Robson Schwartz

Activity Recognition based on a Magnitude-Orientation Stream Network Inproceedings

In: Conference on Graphics, Patterns and Images (SIBGRAPI), pp. 1-8, 2017.

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Carlos Antonio Caetano Junior; Jefersson A dos Santos; William Robson Schwartz

Optical Flow Co-occurrence Matrices: A Novel Spatiotemporal Feature Descriptor Inproceedings

In: IAPR International Conference on Pattern Recognition (ICPR), pp. 1-6, 2016.

Links | BibTeX