Reflective Feature Detection and Hierarchical Reflection Separation in Image Sequences

Di Yang (ANU)

COMPUTER VISION AND ROBOTICS SERIES

DATE: 2013-11-20
TIME: 10:00:00 - 11:00:00
LOCATION: RSISE Seminar Room, ground floor, building 115, cnr. North and Daley Roads, ANU
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ABSTRACT:
Computer vision techniques such as Structure-from-Motion (SfM) and object recognition tend to fail on scenes with highly reflective objects because the reflections behave differently to the true geometry of the scene. Such image sequences may be treated as two layers superimposed over each other - the non-reflection scene source layer and the reflection layer. However, decomposing the two layers is a very challenging task as it is ill-posed and common methods rely on prior information. In our works, we present an automated technique for detecting reflective features with a comprehensive analysis of the intrinsic, spatial, and temporal properties of feature points. A support vector machine (SVM) is proposed to learn reflection feature points. Predicted reflection feature points are used as priors to guide the reflection layer separation. This gives more robust and reliable results than what is achieved by performing layer separation alone. Moreover, this technique could be used to help us eliminate interference of reflections so as to possibly enable us to detect bend and dent in vehicle panels.
BIO:
http://people.cecs.anu.edu.au/user/3497