Stereo Matching as a Nearest-Neighbor Problem
نویسندگان
چکیده
We propose a representation of images, called intrinsic curves, that transforms stereo matching from a search problem into a nearest-neighbor problem. Intrinsic curves are the paths that a set of local image descriptors trace as an image scanline is traversed from left to right. Intrinsic curves are ideally invariant with respect to disparity. Stereo correspondence then becomes a trivial lookup problem in the ideal case. We also show how to use intrinsic curves to match real images in the presence of noise, brightness bias, contrast fluctuations, moderate geometric distortion, image ambiguity, and occlusions. In this case, matching becomes a nearest-neighbor problem, even for very large disparity values.
منابع مشابه
Non-zero probability of nearest neighbor searching
Nearest Neighbor (NN) searching is a challenging problem in data management and has been widely studied in data mining, pattern recognition and computational geometry. The goal of NN searching is efficiently reporting the nearest data to a given object as a query. In most of the studies both the data and query are assumed to be precise, however, due to the real applications of NN searching, suc...
متن کاملOptimizing Disparity Candidates Space in Dense Stereo Matching
In this paper, a new approach for optimizing disparity candidates space is proposed for the solution of dense stereo matching problem. The main objectives of this approachare the reduction of average number of disparity candidates per pixel with low computational cost and high assurance of retaining the correct answer. These can be realized due to the effective use of multiple radial windows, i...
متن کاملImproving Text Normalization by Optimizing Nearest Neighbor Matching
Text normalization is an essential task in the processing and analysis of social media that is dominated with informal writing. It aims to map informal words to their intended standard forms. In this paper, we present an automatic optimization-based nearest neighbor matching approach for text normalization. This approach is motivated by the observation that text normalization is essentially a m...
متن کاملA comparison of 12 algorithms for matching on the propensity score
Propensity-score matching is increasingly being used to reduce the confounding that can occur in observational studies examining the effects of treatments or interventions on outcomes. We used Monte Carlo simulations to examine the following algorithms for forming matched pairs of treated and untreated subjects: optimal matching, greedy nearest neighbor matching without replacement, and greedy ...
متن کاملAsymptotic Behaviors of Nearest Neighbor Kernel Density Estimator in Left-truncated Data
Kernel density estimators are the basic tools for density estimation in non-parametric statistics. The k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in which the bandwidth is varied depending on the location of the sample points. In this paper, we initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- IEEE Trans. Pattern Anal. Mach. Intell.
دوره 20 شماره
صفحات -
تاریخ انتشار 1998