نتایج جستجو برای: random sample consensus ransac
تعداد نتایج: 734071 فیلتر نتایج به سال:
The sponsors for events such as motor sports can install billboard advertisements at event sites in return for investments. Checking how ads appear in a broadcast is important to confirm the effectiveness of investments and recognizing ads in videos is required to make the check automatic. This paper presents a method for recognizing multiple ads. After obtaining point correspondences between a...
This paper presents a novel method to recognize current location of a mobile robot from input stereo images with visual and geometric features. We extract structural planes from 3D depth data by using SLIC (Simple Linear Iterative Clustering) based superpixel and RANSAC algorithm. The experimental results show that the proposed method using visual features and their geometric relationship provi...
A novel idea on how to make RANSAC repeatable is presented, which will find the optimal set in nearly every run for certain types of applications. The proposed algorithm can be used for such transformations that can be constructed by more than the minimal points required. We give examples on matching of aerial images using the Direct Linear Transformation, which requires at least four points. M...
This paper presents a probabilistic framework of assembling detected human body parts into a full 2D human configuration. The face, torso, legs and hands are detected in cluttered scenes using boosted body part detectors trained by AdaBoost. Body configurations are assembled from the detected parts using RANSAC, and a coarse heuristic is applied to eliminate obvious outliers. An a priori mixtur...
We reconsider the classic problem of estimating accurately a 2D transformation from point matches between images containing outliers. RANSAC discriminates outliers by randomly generating minimalistic sampled hypotheses and verifying their consensus over the input data. Its response is based on the single hypothesis that obtained the largest inlier support. In this article we show that the resul...
We introduce the problem of autonomous trail following without waypoints and present a visionand ladar-based system which keeps to continuous hiking and mountain biking trails of relatively low human difficulty. Using a RANSAC-based analysis of ladar scans, trail-bordering terrain is classified as belonging to one of several major types: flat terrain, which exhibits low height contrast between ...
Most approaches to large-scale image retrieval are based on the construction of the inverted index of local image descriptors or visual words. A search in such an index usually results in a large number of candidates. This list of candidates is then re-ranked with the help of a geometric verification, using a RANSAC algorithm, for example. In this paper we propose a feature representation, whic...
In many vision problems (e.g., stereo, motion) multiple structures can occur in the data, in which case several instances of the same model need to be recovered from a single data set. However, once the measurement noise becomes significantly large relative to the separation between the structures, the robust statistical methods commonly used in the vision community tend to fail. In this paper,...
This paper presents a new method to combine local and global features for near-duplicate images detection. It mainly consists of three steps. Firstly, the keypoints of images are extracted and preliminarily matched. Secondly, the matched keypoints are voted for estimation of affine transform to reduce false matching keypoints. Finally, to further confirm the matching, the Local Binary Pattern (...
I n extracting a polynomial surface patch nearan intensity or range discontinuity, a robust estimator must tolerate not only the truly random bad data (“random outliers”), but also the coherently structured points ((bseudo outliers”) that belong to a different surface. To characterize the performance of least median of squares, M-estimators, Hough transforms, RANSAC, and MINPRAN on data contain...
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