OPTIMOL: automatic Object Picture collecTion

via Incremental MOdel Learning

a chicken and egg problem…

…among users, researchers, and data

ImagesImages

e.g. Caltech101,LabelMe, LHI

Framework

Category model

Classification

Dataset

Keyword: accordion Li, Wang & Fei-Fei, CVPR 2007

Framework

Category model

Classification

Dataset

Keyword: accordion Li, Wang & Fei-Fei, CVPR 2007

…

Compute SIFT descriptor

[Lowe’99]

Image representationImage representation

Kadir&Brady interest point detector

Codewords representatio

n

Nonparametric topic model-Hierarchical Dirichlet Process (HDP)

MN

Each patch

Each image

Teh, et al. 2004; Sudderth et al. CVPR 2006; Wang, Zhang & Fei-Fei, CVPR 2006

Nonparametric topic model-Hierarchical Dirichlet Process (HDP)

MN

Teh, et al. 2004; Sudderth et al. CVPR 2006; Wang, Zhang & Fei-Fei, CVPR 2006

Li, Wang & Fei-Fei, CVPR 2007

Classification

Likelihood ratio for decision:

Category likelihood for I:

Li, Wang & Fei-Fei, CVPR 2007

Annotation

Pitfall #1: model drift

Object Model

…

Object Model

…

Li, Wang & Fei-Fei, CVPR 2007

Object Model

Good Images

Bad Images

…

Pitfall #2: model diversity

Li, Wang & Fei-Fei, CVPR 2007

The “cache set”

Li, Wang & Fei-Fei, CVPR 2007

CategoryModel

classification

Enlarged dataset

Cache

Raw image dataset

Incrementallearning

Result

Li, Wang & Fei-Fei, CVPR 2007

Li, Wang & Fei-Fei, CVPR 2007

Li, Wang & Fei-Fei, CVPR 2007

OPTIMOL also learns good models

Team OPTIMOL (UIUC-Princeton):

11stst Place Place in the Software League