Metodologia de Pesquisa Científica

Prof. Dr. Gilberto Câmara

Aluno: Felipe Correa

Análise de Tese:

EMPLOYING CITIZEN SCIENCE

TO

LABEL POLYGONS

OF SEGMENTED IMAGES

Tese da aluna

Marinalva Soares, orientada pelo

Dr. Rafael Santos e Dr. Luciano Dutra

“The proposal is to use untrained and unpaid

volunteer users, regardless of their expertise,

to address the problem of labeling by hand

polygons of different classes resulting from

the urban image segmentation. Urban image

was used as a case study because contains

several types of targets, but the approach

proposed can be applied to non-urban

scenes.”

Citizen Science

Citizen Science is the term used for projects relaying on volunteers

to handle or perform related research tasks, such as observations,

measurements and computational.

Segmented Images

Segmentation can be defined as the process that partitions an image into regions that

cover it (SHAPIRO; STOCKMAN, 2001; JUNG, 2007), so that the elements belonging

to each region are similar with respect to one or more properties.

PROBLEMA

HIPÓTESE

EXPERIMENTO

RESULTADOS E CONCLUSÕES

PROBLEMA

HIPÓTESE

EXPERIMENTO

RESULTADOS E CONCLUSÕES

Problemas:

(i) a time consuming activity for a single expert to

visually label all polygons

(ii) an expensive activity if more experts are hired

to speeden the process of

labeling polygons.

PROBLEMA

HIPÓTESE

EXPERIMENTO

RESULTADOS E CONCLUSÕES

Hipótese:

Humans may interpret scenes without much effort,

since they can use knowledge, experience and

visual evidence including the context of objects in

the image, i.e., they can label most objects

correctly using different types of information

which are applicable to different features or

elements on the image being interpreted.

PROBLEMA

HIPÓTESE

EXPERIMENTO

RESULTADOS E CONCLUSÕES

Experimento:

First Phase: Random Presentation of the Polygons

- …non-repeated labels…

Second Phase: Presentation of Known Polygons

- …polygons are causing more confusion…

- …volunteers’ reliability (test)…

- General majority X Expert’s opinion

Third Phase: Presentation of the Polygons per Class

- …ability to recognize polygons of a given class…

- …non-randomness of the classes influenced the users’ proficiency…

Fourth Phase: Polygons with Regular and Irregular Shape

- …identify whether polygons with irregular shape are harder to label (based on

the polygon’s entropy) than those with more uniform shape…

Fifth Phase: Polygons with Ambiguity

- … high entropy on their labels (polygons from different classes)…

PROBLEMA

HIPÓTESE

EXPERIMENTO

RESULTADOS E CONCLUSÕES

Resultados:

…These analyses showed that it is possible to use citizen

science for labeling polygons and also showed that most of

the labelings made by the volunteers are not guesses.

Multiple labelings performed per polygon (covering different

classes of objects) and per user also enabled conducting

analyses of opinions in order to identify the labels and users

reliable to validate the method.

Análise final: Pontos positivos

1. Boa revisão bibliográfica.

2. Relato eficiente da metodologia, permite a

reprodução do experimento

3. Novas métricas para análise de qualidade

dos dados

Análise final: Pontos negativos

1. Faltou detalhar como obter os resultados

(automático ou manual)

2. Falta de estratégia do primeiro experimento