análise de tese: employing citizen science to label...
TRANSCRIPT
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