KEYWORDS: Reliability, Radio propagation, Cameras, 3D image processing, Data modeling, Digital imaging, Electronics engineering, Illumination engineering, Mahalanobis distance, Image processing
Conventional stereo matching methods provide the unsatisfactory results for stereo pairs under uncontrolled environments such as illumination distortions and camera device changes. A majority of efforts to address this problem has devoted to develop robust cost function. However, the stereo matching results by cost function cannot be liberated from a false correspondence when radiometric distortions exist. This paper presents a robust stereo matching approach based on probabilistic Laplacian propagation. In the proposed method, reliable ground control points are selected using weighted mutual information and reliability check. The ground control points are then propagated with probabilistic Laplacian. Since only reliable matching is propagated with the reliability of GCP, the proposed approach is robust to a false initial matching. Experimental results demonstrate the effectiveness of the proposed method in stereo matching for image pairs taken under illumination and exposure distortions.
Bag-of-words (BoW) is one of the most successful methods for object categorization. This paper proposes a statistical
codeword selection algorithm where the best subset is selected from the initial codewords based on the statistical
characteristics of codewords. For this purpose, we defined two types of codeword-confidences: cross- and within-category
confidences. The cross- and within-category confidences eliminate indistinctive codewords across categories and
inconsistent codewords within each category, respectively. An informative subset of codewords is then selected based on
these two codeword-confidences. The experimental evaluation for a scene categorization dataset and a Caltech-101 dataset
shows that the proposed method improves the categorization performance up to 10% in terms of error rate reduction when
cooperated with BoW, sparse coding (SC), and locality-constrained liner coding (LLC). Furthermore, the codeword size
is reduced by 50% leading a low computational complexity.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.