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In the paper, different variations of solving the problem of the visual odometry for a mobile robot with short-baseline stereo camera are investigated, and a conclusion on the suitability of the approaches considered is done.
Quantitative analysis and motion estimation of the moving organs, as the heart and lungs, is one of the main objectives pursued in analysis of medical images. In fact, cardiac motion estimation has been widely used with the segmentation to evaluate the cardiac function and a various approaches of motion estimation have been proposed. In this paper, a comparative study of myocardial motion estimation...
On the fundamental theory of Structure from Motion, we present an algorithm based on 3D-2D motion estimation monocular visual odometry. In order to resolve the problem of 3D-2D motion estimation, which need to maintain a consistent and accurate set of triangulated 3D feature points and to create precisely 3D-to-2D correspondences, and considering the complexity and variability of the outdoor scene...
The combining method of neighborhood and non-neighborhood is proposed to be used for amending the computed results of optical flow, which has improved the robustness of flow estimation. This method uses the estimated frame based on CLG-TV model, carries out the decomposition of structure and texture for the images, proceeds weighted approach for data term and smooth term, uses coarse-to-fine method...
The optical flow is a velocity field that describes the motion of pixels within a sequence (or set) of images. Its estimation plays an important role in areas such as motion compensation, object tracking and image registration. In this paper, we present a novel framework to estimate the optical flow using local all-pass filters. Instead of using the optical flow equation, the framework is based on...
In this paper, we proposed a novel method for three-dimensional motion estimation by combining straight-line and endpoint optical flow. Firstly, the relationship equations of point and straight-line optical flow with the three-dimensional motion velocities are given under the perspective projection model. Then the three-dimensional motion estimation model based on the correspondence of point and straight-line...
The accuracy of optical flow estimation algorithms has been improving steadily by refining the objective function which should be optimized. A novel energy function for computing 2-D optical flow from X-ray CT images is presented. One advantage of the optical flow framework is the possibility to enforce physical constraints on the numerical solutions. The physical constraints which have been included...
Digital image stabilizer (DIS) is an important component of a digital video camera. Its purpose is to compensate video which suffers from camera jitters due to unstable random camera motions (hand held video cameras). In this paper a guide for a general-robust video stabilization algorithm which can remove unwanted motions (translation or rotation) is proposed. First the optical flow between two successive...
Conventional 2D-to-3D conversion approaches always have some problems due to fast motion and non-rigid objects. In this proposed approach, a bi-direction optical flow is used to extract credible corner points from original sequences, and then Mean Shift algorithm helps to segment foreground object. In addition, improved active contour model offers more accurate outlines. Finally depth correlation...
In this paper, the feasibility of super-resolution reconstruction of the deformable tissue from temporal sequences of ultrasound images is extensively studied. The proposed image observation model integrates the non-rigid motion and imaging formation process into a unified super-resolution frame. To facilitate the motion estimation, Lucas-Kanade optical flow is chosen for non-rigid motion estimation...
This paper presents a method to accurately determine the three-dimensional motion of a vehicle based on image pairs acquired with a stereo system. The basic idea is to express the relationship between correspondent features that belong to non moving objects in successive frames as a nonlinear function of rotation and translation parameters. Minimizing the distance between the previously mentioned...
Sequential multi-sensor satellite images are used for the computation of mesoscale surface currents in the Northern and Southern Baltic Proper. Different marine surface films and accumulated algae at the water surface are imaged by the sensors working in the optical, infrared, and microwave part of the electromagnetic spectrum and can thus be used as tracers for the local motion of the sea surface...
Motion vector estimation is an important parameter for video segmentation. Effective video compression can be achieved by choosing a correct approach for the calculation of motion vector. Here in this paper we propose an optical flow motion vector estimation through iterative Lucas-Kanade pyramidal implementation for both large & small motion in image pyramid representation a group of pixel information...
The implementation of Differential Optical Flow Algorithms in detecting human motion still faces great challenges. To date, there are no general approaches that are suitable especially when dealing with dynamic robust environment. As such, in this paper we propose a method that combines the simple partial derivative adopted from Lukas Kanade, the regularization technique by Horn Schunck and the choice...
In this paper we develop a robust and discontinuity-preserving approach based on local and global combined model for the optical flow estimation. Firstly, the local and global optical flow methods are combined to yield dense flow fields that are robust against noise. Then a non-linear diffusion is provided to the model for discontinuity-preserving of optical flow boundary. Simultaneously, a coarse-to-fine...
In this paper, we propose a new region-based method for accurate motion estimation using discrete optimization. In particular, the input image is represented as a tree of over-segmented regions and the optical flow is estimated by optimizing an energy function defined on such a region-tree using dynamic programming. To accommodate the sampling-inefficiency problem intrinsic to discrete optimization...
A new error concealment method based on optical flow is proposed, as a post-processing tool at the decoder side to recover the lost information during the video transmission. The conventional error concealment methods often result in blocking effects because of inaccurate motion vectors estimation. We use the attractive property of optical flow technique on motion estimation to recover the lost block...
Motion estimation provides an attractive choice to cumbersome interface devices for human computer interaction (HCI). Worthy of note, visual recognition of hand gestures can help achieving in an easy and natural way for interaction between human and computer. The interfaces of HCI and other virtual reality systems depend on accurate, real-time hand and fingertip tracking for association between real...
Group action recognition in soccer videos is a challenging problem due to the difficulties of group action representation and camera motion estimation. This paper presents a novel approach for recognizing group action with a moving camera. In our approach, ego-motion is estimated by the Kanade-Lucas-Tomasi feature sets on successive frames. The optical flow is then computed on compensated frames....
This paper suggests using discrete feature displacements and optical flow simultaneously to determine the camera motion and its velocity. This is advantageous when the number of feature correspondences is low or when the feature correspondences are noisy. The reason is that usually the available optical flow data largely outnumbers the available feature correspondences data. It is also advantageous...
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