Search results for "ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION"
showing 10 items of 982 documents
2D/3D Object Recognition and Categorization Approaches for Robotic Grasping
2017
International audience; Object categorization and manipulation are critical tasks for a robot to operate in the household environment. In this paper, we propose new methods for visual recognition and categorization. We describe 2D object database and 3D point clouds with 2D/3D local descriptors which we quantify with the k-means clustering algorithm for obtaining the Bag of Words (BOW). Moreover, we develop a new global descriptor called VFH-Color that combines the original version of Viewpoint Feature Histogram (VFH) descriptor with the color quantization histogram, thus adding the appearance information that improves the recognition rate. The acquired 2D and 3D features are used for train…
Visual tracking with omnidirectional cameras: an efficient approach
2011
International audience; An effective technique for applying visual tracking algorithms to omni- directional image sequences is presented. The method is based on a spherical image representation which allows taking into account the distortions and nonlinear resolution of omnidirectional images. Experimental results show that both deterministic and probabilistic tracking methods can effectively be adapted in order to robustly track an object with an omnidirectional camera.
Static and Dynamic Objects Analysis as a 3D Vector Field
2017
International audience; In the context of scene modelling, understanding, and landmark-based robot navigation, the knowledge of static scene parts and moving objects with their motion behaviours plays a vital role. We present a complete framework to detect and extract the moving objects to reconstruct a high quality static map. For a moving 3D camera setup, we propose a novel 3D Flow Field Analysis approach which accurately detects the moving objects using only 3D point cloud information. Further, we introduce a Sparse Flow Clustering approach to effectively and robustly group the motion flow vectors. Experiments show that the proposed Flow Field Analysis algorithm and Sparse Flow Clusterin…
Homography based egomotion estimation with a common direction
2017
International audience; In this paper, we explore the different minimal solutions for egomotion estimation of a camera based on homography knowing the gravity vector between calibrated images. These solutions depend on the prior knowledge about the reference plane used by the homography. We then demonstrate that the number of matched points can vary from two to three and that a direct closed-form solution or a Gröbner basis based solution can be derived according to this plane. Many experimental results on synthetic and real sequences in indoor and outdoor environments show the efficiency and the robustness of our approach compared to standard methods.
Central catadioptric image processing with geodesic metric
2011
International audience; Because of the distortions produced by the insertion of a mirror, catadioptric images cannot be processed similarly to classical perspective images. Now, although the equivalence between such images and spherical images is well known, the use of spherical harmonic analysis often leads to image processing methods which are more difficult to implement. In this paper, we propose to define catadioptric image processing from the geodesic metric on the unitary sphere. We show that this definition allows to adapt very simply classical image processing methods. We focus more particularly on image gradient estimation, interest point detection, and matching. More generally, th…
A Geometrical Approach for Vision Based Attitude and Altitude Estimation for UAVs in Dark Environments
2012
International audience; This paper presents a single camera and laser system dedicated to the realtime estimation of attitude and altitude for unmanned aerial vehicles (UAV) under low illumination conditions to dark environments. The fisheye camera allows to cover a large field of view (FOV). The approach, close to structured light systems, uses the geometrical information obtained by the projection of a laser circle onto the ground plane and perceived by the camera. We propose some experiments based on simulated data and real sequences. The results show good agreement with the ground truth values from the commercial sensors in terms of its accuracy and correctness. The results also prove i…
Three-Dimensional Integral-Imaging Display From Calibrated and Depth-Hole Filtered Kinect Information
2016
We exploit the Kinect capacity of picking up a dense depth map, to display static three-dimensional (3D) images with full parallax. This is done by using the IR and RGB camera of the Kinect. From the depth map and RGB information, we are able to obtain an integral image after projecting the information through a virtual pinhole array. The integral image is displayed on our integral-imaging monitor, which provides the observer with horizontal and vertical perspectives of big 3D scenes. But, due to the Kinect depth-acquisition procedure, many depthless regions appear in the captured depth map. These holes spread to the generated integral image, reducing its quality. To solve this drawback we …
K-nearest neighbor driving active contours to delineate biological tumor volumes
2019
Abstract An algorithm for tumor delineation in positron emission tomography (PET) is presented. Segmentation is achieved by a local active contour algorithm, integrated and optimized with the k-nearest neighbor (KNN) classification method, which takes advantage of the stratified k-fold cross-validation strategy. The proposed approach is evaluated considering the delineation of cancers located in different body districts (i.e. brain, head and neck, and lung), and considering different PET radioactive tracers. Data are pre-processed in order to be expressed in terms of standardized uptake value, the most widely used PET quantification index. The algorithm uses an initial, operator selected re…
Accurate keyframe selection and keypoint tracking for robust visual odometry
2016
This paper presents a novel stereo visual odometry (VO) framework based on structure from motion, where a robust keypoint tracking and matching is combined with an effective keyframe selection strategy. In order to track and find correct feature correspondences a robust loop chain matching scheme on two consecutive stereo pairs is introduced. Keyframe selection is based on the proportion of features with high temporal disparity. This criterion relies on the observation that the error in the pose estimation propagates from the uncertainty of 3D points—higher for distant points, that have low 2D motion. Comparative results based on three VO datasets show that the proposed solution is remarkab…
Real time UAV altitude, attitude and motion estimation from hybrid stereovision
2012
International audience; Knowledge of altitude, attitude and motion is essential for an Unmanned Aerial Vehicle during crit- ical maneuvers such as landing and take-off. In this paper we present a hybrid stereoscopic rig composed of a fisheye and a perspective camera for vision-based navigation. In contrast to classical stereoscopic systems based on feature matching, we propose methods which avoid matching between hybrid views. A plane-sweeping approach is proposed for estimating altitude and de- tecting the ground plane. Rotation and translation are then estimated by decoupling: the fisheye camera con- tributes to evaluating attitude, while the perspective camera contributes to estimating t…