CMU Talk: Corridor View: Making Indoor Life Easier with Large Image Database

CMU VASC Seminar
Monday, Dec 7, 2009
1:30pm-2:30pm
NSH 1507

Corridor View: Making Indoor Life Easier with Large Image Database
Hongwen "Henry" Kang
Ph.D. Student, Robotics

Abstract:

Indoor environment poses substantial challenges for Computer Vision algorithms, due to the combined patterns that are either highly repetitive (e.g. doors), textureless (e.g. white walls), or temporally changing (e.g. posters, pedestrians). The fundamental challenge we want to tackle is the robust image matching. We proposed two approaches to address this problem, one is an iterative algorithm that combines global/local weighting strategies under bag-of-features model, the other data-mines distinctive feature vectors and uses high dimensional features directly for image matching, without quantization. Both of the approaches demonstrate significant improvements compared to straightforward image retrieval approaches, in highly confusing indoor environment. The proposed image matching techniques have broad applications. We selectively demonstrate two of them for this talk, specifically for vision impaired users living in the office environments. One application is data-driven zoomin; the other application is image composition for object pop-out.