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In the past decade, research in person re-identification (re-id) has exploded due to its broad use in security and surveillance applications. Issues such as inter-camera viewpoint, illumination and pose variations make it an extremely difficult problem. Consequently, many algorithms have been proposed to tackle these issues. To validate the efficacy of re-id algorithms, numerous benchmarking datasets...
We present a comprehensive overview of the stereoscopic Intel RealSense RGBD imaging systems. We discuss these systems' mode-of-operation, functional behavior and include models of their expected performance, shortcomings, and limitations. We provide information about the systems' optical characteristics, their correlation algorithms, and how these properties can affect different applications, including...
Person re-identification (re-id) aims to match a specific person across non-overlapping views of different cameras, which is currently one of the hot topics in computer vision. Compared with image-based person re-id, video-based techniques could achieve better performance by fully utilizing the space-time information. This paper presents a novel video-based person re-id method named Deep Feature Guided...
This paper presents the results of the depth estimation challenge for dense light fields, which took place at the second workshop on Light Fields for Computer Vision (LF4CV) in conjunction with CVPR 2017. The challenge consisted of submission to a recent benchmark [7], which allows a thorough performance analysis. While individual results are readily available on the benchmark web page http://www...
The human blockage problem is an open issue in next- generation wireless access networks using millimeter-wave (mmWave) communications. A proactive base station (BS) handover system leveraging RGB and depth (RGB-D) cameras is proposed for solving the human blockage problem. RGB-D cameras observe mmWave communication ranges, and BS handover is conducted proactively before a human blockage causes serious...
We introduce a method that uses a single camera to localize a vehicle within a pre-constructed map consisting of a voxel occupancy grid and road-line marker positions. Sophisticated mapping hardware is capable of creating high-accuracy 3D maps of road environments, but localizing a vehicle within such maps is one of the challenges at the forefront of automated driving. A solution which is robust to...
Person re-identification is known as matching an individual captured in one or more cameras using a gallery of provided candidates from a different camera view. It is a hard task owing to variations in illumination, viewpoints, poses and small number of annotated training individuals. For obtaining the proper distance metrics, we propose a novel approach based on dictionary learning. Our method decomposes...
In the context of optical-aided navigation and visual Simultaneous Localization And Mapping (SLAM) for satellite-denied aircraft navigation, this paper extends the monocular SLAM approach by the use of multiple sensors with different viewing directions. Downward optical sensors see other movements than forward-looking cameras, hence it is straightforward to combine the benefits of both. This combination...
Person re-identification is an important task of matching pedestrians across non-overlapping camera views. In this paper, we exploit a weighted feature descriptor for person re-identification. We firstly compute the weights on the superpixel level via graph-based manifold ranking algorithm, then integrate the computed weights into a patch-based feature descriptor, named local maximal occurrence. Finally,...
This paper proposes a new spatio-temporal appearance feature named Phasic Maximal and Local Maximal Occurrence (PM-LOMO) representation for video-based person re-identification. To perform temporal alignment of the sequence, we selected the optimal period of walking cycle and divide frames into several phases based on the extreme points of the sequence's Flow Energy Profile (FEP). To describe the...
Service robots have been widely adopted to the domestic environment over the past few years. Pertaining to this sudden growth, a high interest has been exerted upon the service robots deployed in the domestic circle. The domestic users are not overly cohabitated with technology and use natural language habitually in their daily tasks. Instead of a set of machine specific instructions, natural language...
The paper presents a method for obtaining a surface gradient using photometric stereo method. A described technique deals with the limitations of the photometric stereo method to make it more suitable for use in industrial, rather than laboratory conditions. The image is captured with a RGB camera paired with a light source which light direction and wavelength composition can be externally controlled...
In this work a preliminary study is proposed to assess the validity of an automatic and low cost measurement method for Functional ReachTest (FRT) implementation. To this aim FRT was performed on 10 trials of 4 healthy men and results from the system under validation are compared with the corresponding data from a calibrated stereo-photogrammetric system: the percentage variation between them is lower...
We propose an active exposure control method to improve the robustness of visual odometry in HDR (high dynamic range) environments. Our method evaluates the proper exposure time by maximizing a robust gradient-based image quality metric. The optimization is achieved by exploiting the photometric response function of the camera. Our exposure control method is evaluated in different real world environments...
In this paper, a monocular vision measurement method based on rotating lens is proposed. A special optical lens is placed between the target and the camera, which causes light refraction during the measurement process. By analyzing images taken after different light refraction, the 3D coordinates of the target can be obtained. Using this method, 3D measurement of the full field can be completed with...
Horizon or skyline detection plays a vital role towards mountainous visual geo-localization, however most of the recently proposed visual geo-localization approaches rely on user-in-the-loop skyline detection methods. Detecting such a segmenting boundary fully autonomously would definitely be a step forward for these localization approaches. This paper provides a quantitative comparison of four such...
Light field technology may have a positive impact on several multimedia applications thanks to novel ways to explore the captured scenes, such as changing the parallax (horizontally and vertically) and refocusing the content. These innovative use cases require new considerations that affect the whole processing chain, from content acquisition to visualization, as well as the methodologies for quality...
In this paper we investigate an emerging application, 3D scene understanding, likely to be significant in the mobile space in the near future. The goal of this exploration is to reduce execution time while meeting our quality of result objectives. In previous work, we showed for the first time that it is possible to map this application to power constrained embedded systems, highlighting that decision...
In this study, the motion blur caused by the variable speed egomotion of camera is deblurred using multiple image frames and the obtained results are compared based on the detection performance of corner features. A linear, uniform motion blur data set is collected which is suitable for testing the multi-image deblurring method. The proposed method is tested on the dataset together with two baseline...
As a fundamental task in automated video surveillance, person re-identification, which has received increasing attention in recent years, aims to match people across non-overlapping camera views in a multi-camera surveillance system. It has been reported that KISS metric learning has been followed by most of the previous supervised work because of its state of the art performance for person re-identification...
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