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The traditional triangulation algorithms in multiview geometry problems have the drawback that its solution is locally optimal. Robust Optimization is a specific and relatively novel methodology for handling optimization problems with uncertain data. The key idea of robust optimization is to find the best possible performance in the worst case. In this paper, we propose a novel approach which solves...
In this paper, we develop a way to accurately and precisely estimate the pose of a calibrated camera with a single picture which includes a known planar object. For the proposed algorithm, we first use SURF detector for feature extraction and matching. Then, we use the information from known reference image to retrieve 3D point coordinates. Based on resulting 2D-2D correspondences and 3D coordinates,...
A robust omni-directional vision based localization method that allows us to obtain accurate mobile robot pose of large indoor environments is proposed. To implement the localization based on vision. In a learning step, the robot is manually guided on a path and an omni-directional image frames sequence is recorded. From this sequence a topological map is built with robust affine and scale invariant...
Based on the Lucas-Kanade optical flow method, a dynamically selecting model is proposed in this paper to track a moving object. This model is composed of an object model, a consistency constraint model, and a random sampling model. Based on the current image frame, the object model is used to calculate the relevant feature points for the next frame. The random sampling model is used to resample the...
In this paper a new lane marking detection algorithm in different road conditions for monocular vision was proposed. Traditional detection algorithms implement the same operation for different road conditions. It is difficult to simultaneously satisfy the requirements of timesaving and robustness in different road conditions. Our algorithm divides the road conditions into two classes. One class is...
This paper presents an analysis on stability robustness of the widely used nonlinear dynamic inversion algorithm. By using nonlinear dynamic inversion algorithm, the multiple-inputs-multiple-outputs affine nonlinear system which has bounded uncertainty and disturbances is transformed into a linear time varying system with special structure. Thus the stability robustness issues of nonlinear dynamic...
In this paper, we propose online metric learning tracking method that consider visual tracking as a similarity measurement problem, and incorporates adaptive metric learning and generative histogram model based on non-sparse linear representation into the target tracking framework. We propose a generative histogram model based on non-sparse linear representation, which make full use of the non-sparse...
The homography between image pairs are normally estimated by minimizing a suitable cost function given 2D keypoints correspondences. The correspondences are typically established using descriptor distance of keypoints. However, the correspondences are often incorrect due to ambiguous descriptors which can introduce errors into following homography computing step. There have been numerous attempts...
In this paper, we propose a novel approach based on online learning for accurate and effective detection of abandoned objects. Most existing methods for abandoned objects detection only detect abandoned objects without considering of the logic owner of the abandoned object. These methods need an advanced trained human detector to discriminate abandoned objects from still persons frequently. However,...
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