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Accurate and robust environment perception is a prerequisite for advanced driver assistance systems such as parking assistance, collision avoidance or night vision systems but also for robot navigation. In this context, occupancy grid mapping is a common way to represent the static car surroundings perceived by radar, laser or camera sensors. This work focuses on the challenges of nighttime grid mapping...
Nocturnally migratory birds and bats are at higher risk of colliding with wind turbines. It is important to gather scientific data in an area which have potential of wind farm development. An IR camera recording and its analysis can provide necessary information to wildlife biologists involve with interaction of birds/bats with wind turbines. An efficient IR video processing algorithm has been developed...
This research proposes a novel scheme for vision-aided inertial navigation based on planar homography. By exploiting the multiplicative group property of homography matrices, extended Kalman filter-based vision aiding is formulated with a measurement model of the group difference between image-estimated and navigation homographies. A simple compensation for depth distortion of the homography matrix...
Obstacle avoidance is a key feature for automotive navigation that requires an accurate representation of the environment. In the field of visual perception this task has often been addressed with stereo algorithms that try to obtain a depth map of the environment via disparity calculations on a single pair of images. These algorithms do not exploit that especially in automotive scenarios the fields...
Intrinsic calibration, i.e. finding the mapping between a camera's image positions and corresponding view rays, is a cumbersome, yet unavoidable task in order to accurately generate and interpret results from many kinds of image processing algorithms. We address this problem in the context of vehicle-mounted cameras with arbitrary fields of view with applications in advanced driver assistance systems...
This paper presents a novel method for extrinsic parameters estimation of a single line scan LiDAR and a camera. Using a checkerboard, the calibration setup is simple and practical. Particularly, the proposed calibration method is based on resolving geometry of the checkerboard that visible to the camera and the LiDAR. The calibration setup geometry is described by planes, lines and points. Our novelty...
Estimating surface normals is an important task in computer vision, e.g. in surface reconstruction, registration and object detection. In stereo vision, the error of depth reconstruction increases quadratically with distance. This makes estimation of surface normals an especially demanding task. In this paper, we analyze how error propagates from noisy disparity data to the orientation of the estimated...
It can be difficult to compare the merits of cameras using different sensor technologies using only the specifications typically provided by the manufacturers. The Noise Equivalent Irradiance (NEI) provides a normalized and unique parameter allowing a direct comparison. It is also fairly simple to calculate from the commercial specifications for a given wavelength and exposure time of interest. We...
Stereo visual odometry (VO) is a common technique for estimating a camera's motion, features are tracked across frames and the pose change is subsequently inferred. This position estimation method can play a particularly important role in environments in which the global positioning system (GPS) is not available (e.g., Mars rovers). Recently, some authors have noticed a bias in VO position estimates...
A method for detecting local defects in moulded plastic parts is presented. The method uses deflectometry to produce a contrast enhanced image that is later processed in a novel algorithm. The method operates without the need for accurate mechanical models and is robust to changes in image resolution. Experimental results show that the method can detect subtle defects with over 90% accuracy on most...
Collision avoidance for small unmanned aerial vehicles operating in a variety of environments is limited by the types of available depth sensors. Currently, there are no sensors that are lightweight, function outdoors in sunlight, and cover enough of a field of view to be useful in complex environments, although many sensors excel in one or two of these areas. We present a new depth estimation method,...
This paper presents the use of a low-cost quadrotor applied for visual detection of landmine-like objects. Nowadays, landmines in Colombia are harmful and even letal artifacts mostly abandoned in rural areas. A percentage of the overall number of landmines are hand-crafted and partially exposed on the terrain's surface so that they can be triggered. Based on that fact, we propose an artificial vision...
The development of an object tracking controller for a quadcopter using an on-board vision system is presented. Using low-cost components, a novel system is introduced that operates entirely on board the quadcopter, without external localization sensors or GPS. A low-frequency monocular computer vision algorithm is applied in closed-loop control to track an object of known color. Parallel PID controllers...
We address motion de-blurring using a computational camera that captures an image while the stabilizing optical element moves in a modified Canon IS lens. Our work builds on that of Levin et al. [11], who introduce parabolic motion as a means of achieving invariance to unknown subject velocity in an a priori known direction. While the previous work addresses a specific scenario - exact knowledge of...
In this paper, we explore the possibility to solve a commonly-known digital image forensics problem, the Source Camera Identification (SCI) problem, using a distributed approach. The SCI problem requires to recognize the camera used to acquire a given digital image, distinguishing even among cameras of the same brand and model. The solution we present is based on the algorithm by Lukas Fridrich, as...
Building high dynamic range (HDR) images by combining photographs captured with different exposure times present several drawbacks, such as the need for global alignment and motion estimation in order to avoid ghosting artifacts. The concept of spatially varying pixel exposures (SVE) proposed by Nayar et al. enables to capture in only one shot a very large range of exposures while avoiding these limitations...
This paper presents a novel method to perform the outlier rejection task between two different views of a camera rigidly attached to an Inertial Measurement Unit (IMU). Only two feature correspondences and gyroscopic data from IMU measurerments are used to compute the motion hypothesis. By exploiting this 2-point motion parametrization, we propose two algorithms to remove wrong data associations in...
Unlike the traditional feature-based methods, we propose using motion vectors (MVs) from video streams as inputs for visual navigation. Although MVs are very noisy and with low spatial resolution, MVs do possess high temporal resolution which means it is possible to merge MVs from different frames to improve signal quality. Homography filtering and MV thresholding are proposed to further improve MV...
We introduce the Imperial College London and National University of Ireland Maynooth (ICL-NUIM) dataset for the evaluation of visual odometry, 3D reconstruction and SLAM algorithms that typically use RGB-D data. We present a collection of handheld RGB-D camera sequences within synthetically generated environments. RGB-D sequences with perfect ground truth poses are provided as well as a ground truth...
This paper proposes a novel method to estimate relative poses for a calibrated stereo camera. Three corresponding points in 3D space are theoretically required to recover unconstraint motion which has six degrees of freedom. The proposed method solves this problem with only two 3D points by exploiting a common reference direction between poses. Two points are selected in accordance with the distance...
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