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Lateral localization of an autonomous vehicle within its lane is major information for its adequate control and navigation. Computer vision and robotics communities have used primarily images to Bird's Eye View for easier data manipulation than perspective image. Nevertheless, this technique usually assumes that the terrain is flat and needs calibration for its transformation matrix. In this paper...
In this paper we propose a post-processing method for block-matching based correspondence vector fields. We combine image adaptive filtering for object accurate vector field refinement with differential floating point precise optical flow estimation. More precisely, image warping and large cross-adaptive filter kernels are integrated into the Horn and Schunck optical flow estimation approach to break...
In this paper, an unobtrusive, fully-automated, model-based algorithm is proposed, which is able to estimate the pose of a cyclist and track it over time to extract important pose and movement parameters. Applied techniques include background subtraction, skin detection, principal component analysis and template matching. The proposed algorithm is robust against variations in human appearance such...
Wireless Capsule Endoscopy (WCE) is progressively emerging as one of the most popular non-invasive imaging tools for gastrointestinal (GI) tract inspection. As a critical component of capsule endoscopic examination, physicians need to know the precise position of the endoscopic capsule in order to identify the position of intestinal disease. For the WCE, the position of the capsule is defined as the...
This paper presents a coarse-to-fine combined method for dealing with large displacement situations caused by low speed of frame rate in microscopic video sequences. Motion image estimation method utilizes the modified block matching method based on image warping to perform a wide range of changes in the amount of search comparison, and then using the optical flow method to fine adjustment pixel by...
Image processing techniques for the removal of haze such as smoke and fog from digital images have been actively researched. In the haze removing from an image, it is necessary to estimate the transmission map and the global atmospheric light in the image. The authors have proposed the estimation method based on the minimum and maximum bilateral filters. However, the computational cost of the filters...
Human pose estimation in monocular still image is a hotspot and difficult issue in the computer vision field, and it has important applicable to many novel area. However, the detecting rate is still poor due to many factors as variety of pose and clothing, occlusion, clustering background etc. A pose estimation approach combining deformable part model and full body model is presented to solve the...
Tree models for human pose estimation have been prevailed in the last decade, which are effective in human pose estimation. This paper aims to incorporate the appearance symmetry of human limb parts into tree model and address the problem of the wrong detection of human limbs. For a pair of symmetrical limbs, such as for legs and arms, their appearances are similar that can use a distance to represent...
This paper proposes an attitude estimation method only based on optical flow and achieves the attitude tracking for a three degree-of-freedom (3-DOF) lab helicopter. The relation between optical flow and the motion of the helicopter is derived from the transformation between the image coordinate and the world coordinate. Then, the attitude information is acquired by solving nonlinear equations. Experiment...
This paper presents a fast and accurate auto white balance scheme specifically suited for white balance (WB) correction in digital pathology applications. The scheme uses low-level statistics based technique for illuminant estimation and linear transformation method for image correction. The WB performance of the proposed scheme has been tested in various real life conditions and found to be within...
Pedestrian flow estimation is a vital issue in video surveillance. Inspired by fluid mechanics we proposed to model the pedestrian flow as time-dependent fluid, and estimate the pedestrian flow using flux. Firstly, optical flow is used to construct the motion vector field. Then, we compute the inside and outside flux components within fixed areas to estimate the pedestrian flow in different direction...
This paper proposes a new method for tracking with accurate scale estimation using motion vector errors. First we estimate an object displacement vector using the set of inlier motion vectors(VMF) filtered out by Median Flow tracker [2]. Then we calculate each motion vector error, i.e. the distance between each VMF and the estimated object displacement vector. 50 percent of VMF with large motion vector...
We propose an efficient algorithm for motion deblurring with kernel estimation using consecutive images. First we estimate motion vectors between consecutive images using optical flow and RANSAC. Then we calculate the weights of motion vectors. The proposed method is similar to Ben-Ezra's method. The main difference is that we use a single camera for estimating a blur kernel and capturing a blurred...
Real-time pose estimation and reliable motion control are two crucial tasks for a quadrotor UAV. In order to obtain accurate and robust pose estimation, an estimation algorithm based on Cubature Kalman Filter (CKF) is adopted in this paper. Considering the limitation of a quadrotor working in GPS-denied indoor environments, a sparse optical flow algorithm is utilized in our work to estimate the quadrotor's...
In this paper, we tackle the problem of mapping multiple 3D rigid structures and estimating their motions from perspective views through a car-mounted camera. The proposed method complements conventional localization and mapping algorithms (such as Visual Odometry and SLAM) to estimate motions of other moving objects in addition to the vehicle's motion. We present a theoretical framework for robust...
Factor graphs are a general estimation framework that has been widely used in computer vision and robotics. In several classes of problems a natural partition arises among variables involved in the estimation. A subset of the variables are actually of interest for the user: we call those target variables. The remaining variables are essential for the formulation of the optimization problem underlying...
In computer vision, tracking human pose has received a growing attention in recent years. The existing methods used multi-view videos and camera calibrations to enhance the shape of the object in 3D view. In this paper, tracking and partial reconstruction of the shape of the object from a single view video is identified. The goal of the proposed integrated method is to detect the movement of a person...
In crowd surveillance systems, it is important to select the proper analysis algorithm considering the properties of the video content. The inappropriate algorithm selection may result in performance degradation and generation of false alarms. An important feature of crowd videos is the density of the crowd. While object detection and tracking based algorithms are feasible for low density crowds,...
The research is focused on depth evaluation using a single camera. 2D images can be used for finding the depth of a particular object in the image. Algorithm uses marker(s) to update its orientation and to compute the distance. Initially the shape of the marker is fixed and is pre-defined but as the research expands improvements will make the algorithm to work autonomously using everyday objects as...
We present an approach which enables real-time augmentation of an environment composed of materials with different texture and reflectance properties without the need of application-specific hardware or extensive preparation. Our solution uses a set of RGB images of a reconstructed model to optimize the reflectance parameters and light location. Each image is decomposed into its specular and diffuse...
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