The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Camera calibration has many applications in various computer vision fields such as pose estimation, robot navigation, trajectory tracking, and object recognition. Camera calibration involves (mostly) determining the intrinsic parameters of a camera so that problems or distortions caused by the camera's optics or manufacturing could be estimated for proper projection. There are already a number of...
This study focuses on effects of uniform and full height map correction methods for dewarping book spread images in an automated book reader design for individuals with visual impairment and blindness. The design concept could also be applied to address the challenging process of book digitization. The method is dependent on the geometry of the book reader setup for acquiring the 3-D maps that yield...
The growing interest for mobile biometrics stems from the increasing need to secure personal data and services, which are often stored or accessed from there. Modern user mobile devices, with acquisition and computation resources to support related operations, are nowadays widely available. This makes this research topic very attracting and promising. Iris recognition plays a major role in this scenario...
Understanding where people attention focuses is a challenging and extremely valuable task that can be solved using computer vision technologies. In this paper we address this problem on surveillance-like scenarios, where head and body imagery are usually low resolution. We propose a method to profile the attention of people moving in a known space. We exploit coarse gaze estimation and a novel model...
In this paper, a method for unknown object tracking in output images from 360-degree cameras called Modified Training-Learning-Detection (MTLD) is presented. The proposed method is based on the recently introduced Training-Learning-Detection (TLD) scheme in the literature. The flaws of the TLD approach have been detected and significant modifications are proposed to enhance and to elaborate the scheme...
Most Wide Area Motion Imagery (WAMI) based trackers use motion based cueing for detecting and tracking moving objects. The results are very high false alarm rates in urban environments with tall structures due to parallax effects. This paper proposes an accurate moving object detection method using a precise orthorectification approach for ground stabilization combined with accurate multiview depth...
Pedestrian detection from in-vehicle camera images for the purpose of advanced driver assistance systems is of particular importance in cases of low-resolution pedestrians, because it is desirable to detect the pedestrian as far from the vehicle as possible to effectively provide safe driving support for the driver. Most previous studies on pedestrian detection, however, have focused on pedestrians...
Deep learning is greatly successful when used for pedestrian detection. However, we find that this method is barely satisfactory for multi-scale detection. Meanwhile, various solutions such as multi-scale classifiers have been developed (based on traditional methods) to handle this situation. Considering this, we propose a scale-discriminative classifier layer (SDC) that contains numerous classifiers...
In this paper, we describe how to establish an embedded framework for real-time top-view people counting. The development of our system consists of two parts, i.e. establishing an embedded signal processing platform and designing a people counting algorithm for the embedded system. For the hardware platform construction, we use Kinect as the camera and exploit NVIDIA Jetson TK1 board as the embedded...
4-D Light field information, of which we can extract the target depth information, can be obtained with only one photo using light field camera. The existing target depth information acquisition methods based on light field mostly need huge amounts of photographs and complicated mathematical calculations. To solve these problems, this paper puts forward a light-field-based depth measurement method,...
A technique for the acquisition of an increased number of pupil positions, using a combined sensor consisting of a low-rate camera and a high-rate optical sensor, is presented in this paper. The additional data are provided by the optical movement-detection sensor mounted in close proximity to the eyeball. This proposed solution enables a significant increase in the number of registered fixation points...
Thin leaves, fine stems, self-occlusion, non-rigid and slowly changing structures make plants difficult for three-dimensional (3D) scanning and reconstruction - two critical steps in automated visual phenotyping. Many current solutions such as laser scanning, structured light, and multiview stereo can struggle to acquire usable 3D models because of limitations in scanning resolution and calibration...
In recent years, the use of imaging based, non-invasive, and non-destructive plant phenotyping platforms have become popular. The analysis of the imaging data acquired from these platforms is still challenging. Current, 2D methods are limited in the information available, while 3D methods are more challenging to analyze. Plants like wheat are particularly challenging due to their thin leaves which...
In this paper, a panoramic image stitching algorithm is presented. The aim of image stitching is to detect several images of the same scene and merge them to create a larger image. This is achieved by first detecting the overlapping area of the acquired images, and then aligning and blending the seams of the images automatically to create a seamless panoramic image. The experimental testing into the...
Analysis of near-infrared images has a possibility to simply find vein disease. If super-resolution (SR) techniques improve the quality of near-infrared images with a low signal-to-noise ratio, they could detect abnormal veins at an early stage. Deep convolutional neural networks (DCNNs) as a SR technique were applied to downgraded images, and the effectiveness was investigated. The DCNNs with the...
Existing approaches to object detection address the generation of object hypotheses by extracting several cues in natural and automotive images, relying on objects with sufficiently high resolution. Very little to almost no approaches, however, address the generation of hypothesis of very small or distant objects in images such as on motorways. Here, we propose a simple yet effective approach to generating...
With the advent of commodity autonomous mobiles, it is becoming increasingly prevalent to recognize under extreme conditions such as night, erratic illumination conditions. This need has caused the approaches using multi-modal sensors, which could be complementary to each other. The choice for the thermal camera provides a rich source of temperature information, less affected by changing illumination...
This paper addresses the design of a partitioned vision-guided scheme for repetitive optical biopsies. More precisely, our approach uses two image modalities to perform 6 degrees of freedom (DOF) positioning task. The development aims to partition the control into 3 DOF controlled by the B-scan images acquired with an optical coherence tomography (OCT) system and the remaining 3 DOF controlled by...
We consider the question of benchmarking the performance of methods used for estimating the depth of a scene from a single image. We describe various measures that have been used in the past, discuss their limitations and demonstrate that each is deficient in one or more ways. We propose a new measure of performance for depth estimation that overcomes these deficiencies, and has a number of desirable...
Depth restoration, the task of correcting depth noise and artifacts, has recently risen in popularity due to the increase in commodity depth cameras. When assessing the quality of existing methods, most researchers resort to the popular Middlebury dataset, however, this dataset was not created for depth enhancement, and therefore lacks the option of comparing genuine low-quality depth images with...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.