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Learning based methods have shown very promising results for the task of depth estimation in single images. However, most existing approaches treat depth prediction as a supervised regression problem and as a result, require vast quantities of corresponding ground truth depth data for training. Just recording quality depth data in a range of environments is a challenging problem. In this paper, we...
This paper addresses the problem of spatio-temporal alignment of multiple video sequences. We identify and tackle a novel scenario of this problem referred to as Nonoverlapping Sequences (NOS). NOS are captured by multiple freely panning handheld cameras whose field of views (FOV) might have no direct spatial overlap. With the popularity of mobile sensors, NOS rise when multiple cooperative users...
Structure-from-Motion (SfM) methods can be broadly categorized as incremental or global according to their ways to estimate initial camera poses. While incremental system has advanced in robustness and accuracy, the efficiency remains its key challenge. To solve this problem, global reconstruction system simultaneously estimates all camera poses from the epipolar geometry graph, but it is usually...
The images taken through glass often capture a target transmitted scene as well as undesired reflected scenes. In this paper, we propose a low-rank matrix completion algorithm to remove reflection artifacts automatically from multiple glass images taken at slightly different camera locations. We assume that the transmitted scenes are more dominant than the reflected scenes in typical glass images...
3D reconstruction of indoor scenes is important for lots of applications like SLAM (Simultaneous Localization and Mapping), VR (virtual reality) and AR (augmented reality) etc. This paper presents a precise and low-cost 3D reconstruction system, which consists of a laser emitter, a monocular camera and a turntable. The system is firstly calibrated to determine the intrinsic and extrinsic parameters...
It is normally challenging to model flowering plants, which is affected by illumination, temperature, moisture, soil, etc. To further improve the accuracy and efficiency of such 3D modeling, a 3D reconstruction method for orchid flower, based on virtual binocular stereo vision, was proposed in this paper, where two cameras with baseline and fixed focal length were applied to constitute a binocular...
A novel 3D image-based indoor localization system integrated with an obstacle removal component is proposed. In contrast with existing state-of-the-art localization techniques focusing on static outdoor or indoor environments, the adverse effects generated by moving obstacles, which are very common in busy indoor spaces, is considered in our work. In particular, this problem is converted into a separation...
3D scene reconstruction from multi-view images has many practical applications, including games, virtual/augmented reality, and digital archives of cultural heritage. In this paper, we introduce a new application in video compression. The proposed idea is to have the decoder reconstruct a 3D scene model based on a subset of decoded frames and then reproject the 3D model to 2D for prediction or reconstruction...
The plenoptic function, also known as the light field or the lumigraph, contains the information about the radiance of all optical rays that go through all points in space in a scene. Since no camera can capture all this information, one of the main challenges in plenoptic imaging is light field reconstruction, which consists in interpolating the ray samples captured by the cameras to create a dense...
Light field imaging is limited in its computational processing demands of high sampling for both spatial and angular dimensions. Single-shot light field cameras sacrifice spatial resolution to sample angular viewpoints, typically by multiplexing incoming rays onto a 2D sensor array. While this resolution can be recovered using compressive sensing, these iterative solutions are slow in processing a...
Binary gradient cameras extract edge and temporal information directly on the sensor, allowing for low-power, low-bandwidth, and high-dynamic-range capabilities—all critical factors for the deployment of embedded computer vision systems. However, these types of images require specialized computer vision algorithms and are not easy to interpret by a human observer. In this paper we propose to recover...
The acquisition of partial BRDF measurements using light field cameras and several illumination directions raises critical questions regarding the accuracy of inferences based on that data. Therefore, we attempt to verify the quality of the reconstruction of a full BRDF using partial input data. A dataset that provides a densely sampled BRDF was used, both in viewing and illumination directions. We...
The proliferation of off-the-shelf head-mounted displays (HMDs) let end-users enjoy virtual reality applications, some of which render a real-world scene using a novel view synthesis (NVS) technique. View-dependent texture mapping (VDTM) has been studied for NVS due to its photo-realistic quality. The VDTM technique renders a novel view by adaptively selecting textures from the most appropriate images...
Lenslet images that record both spatial and angular light radiance in a super high definition with distinct macropixel structures desire efficient compression methods for promoting the applications of handheld plenoptic cameras urgently. In this paper, a lenslet image compression method is proposed. First, a reversible image reshaping and adaptive interpolation is proposed to align the macropixel...
We present an anomaly detection system based on an autonomous robot performing a patrol task. Using a generative adversarial network (GAN), we compare the robot's current view with a learned model of normality. Our preliminary experimental results show that the approach is well suited for anomaly detection, providing efficient results with a low false positive rate.
The focus of the project is to create new approaches to the study of the past through the use of innovative aero-space technologies to measure, analyse and reconstruct the ancient landscape and its remaining natural and anthropic traces. The équipe, based at the University of Padua, is constituted by archaeologists, egyptologists, mechanical and software engineers, physicists and computer scientists...
We propose an algorithm for dense and direct large-scale visual SLAM that runs in real-time on a commodity notebook. A fast variational dense 3D reconstruction algorithm was developed which robustly integrates data terms from multiple images. This mitigates the effect of the aperture problem and is demonstrated on synthetic and real data. An additional property of the variational reconstruction framework...
Estimating the 3-D motion of a moving camera from images is a common task in robotics and augmented reality. Most existing marker-less approaches make use of either points or lines. Taking the advantages of both kinds of features in an unknown environment is more attractive due to their availability and differences in characteristics. A novel model-less method is presented in this paper to tackle...
Large scale object is difficult to measure its size because of the complicated shape. The traditional contact measuring method's range is limited, and is not suitable for curved structure. Optical non-contact measurement is a better choice to deal with this situation. Multi-view Reconstruction measurement method is used in this paper. It only uses a digital camera to take pictures of large objects...
Accurate self-localization is a critical problem in autonomous driving system. An autonomous vehicle requires sub-meter level positioning to make motion planning. However, in urban scenarios, the common Global Navigation Satellite System (GNSS) localization suffers from various difficulties as multipath and Non-Line-Of-Sight (NLOS). The Stereo visual odometry proves to be capable of localizing the...
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