In this paper, we study the problem of reproducing the light from a single image of an object covered with random specular microfacets on the surface. We show that such reflectors can be interpreted as a randomized ma...
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ISBN:
(纸本)9781467367592
In this paper, we study the problem of reproducing the light from a single image of an object covered with random specular microfacets on the surface. We show that such reflectors can be interpreted as a randomized mapping from the lighting to the image. Such specular objects have very different optical properties from both diffuse surfaces and smooth specular objects like metals, so we design a special imaging system to robustly and effectively photograph them. We present simple yet reliable algorithms to calibrate the proposed system and do the inference. We conduct experiments to verify the correctness of our model assumptions and prove the effectiveness of our pipeline.
Shadow removal is an important computervision task aiming at the detection and successful removal of the shadow produced by an occluded light source and a photorealistic restoration of the image contents. Decades of ...
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ISBN:
(纸本)9781665448994
Shadow removal is an important computervision task aiming at the detection and successful removal of the shadow produced by an occluded light source and a photorealistic restoration of the image contents. Decades of research produced a multitude of hand-crafted restoration techniques and, more recently, learned solutions from shadowed and shadow free training image pairs. In this work, we propose a single image shadow removal solution via self-supervised learning by using a conditioned mask. We rely on self-supervision and jointly learn deep models to remove and add shadows to images. We derive two variants for learning from paired images and unpaired images, respectively. Our validation on the recently introduced ISTD and USR datasets demonstrate large quantitative and qualitative improvements over the state-of-the-art for both paired and unpaired learning settings.
Image deblurring and super-resolution (SR) are computervision tasks aiming to restore image detail and spatial scale, respectively. Besides, only a few recent works of literature contribute to this task, as conventio...
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ISBN:
(纸本)9781665448994
Image deblurring and super-resolution (SR) are computervision tasks aiming to restore image detail and spatial scale, respectively. Besides, only a few recent works of literature contribute to this task, as conventional methods deal with SR or deblurring separately. We focus on designing a novel Pixel-Guided dual-branch attention network (PDAN) that handles both tasks jointly to address this issue. Then, we propose a novel loss function better focus on large and medium range errors. Extensive experiments demonstrated that the proposed PDAN with the novel loss function not only generates remarkably clear HR images and achieves compelling results for joint image deblurring and SR tasks. In addition, our method achieves second place in NTIRE 2021 Challenge on track 1 of the Image Deblurring Challenge.
When creating a new labeled dataset, human analysts or data reductionists must review and annotate large numbers of images. This process is time consuming and a barrier to the deployment of new computervision solutio...
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ISBN:
(纸本)9781665448994
When creating a new labeled dataset, human analysts or data reductionists must review and annotate large numbers of images. This process is time consuming and a barrier to the deployment of new computervision solutions, particularly for rarely occurring objects. To reduce the number of images requiring human attention, we evaluate the utility of images created from 3D models refined with a generative adversarial network to select confidence thresholds that significantly reduce false alarms rates. The resulting approach has been demonstrated to cut the number of images needing to be reviewed by 50% while preserving a 95% recall rate, with only 6 labeled examples of the target.
In this paper we present a flash game that aims at generating easily ground truth for testing object detection algorithms. Flash the Fish is an online game where the user is shown videos from underwater environments a...
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ISBN:
(纸本)9780769549903
In this paper we present a flash game that aims at generating easily ground truth for testing object detection algorithms. Flash the Fish is an online game where the user is shown videos from underwater environments and has to take photos of fish by clicking on them. The initial ground truth is provided by object detection algorithms and, subsequent, cluster analysis and user evaluation techniques, allow for the generation of ground truth based on the weighted combination of these "photos". Evaluation of the platform and comparison of the obtained results against a hand drawn ground truth confirmed that reliable ground truth generation is not necessarily a cumbersome task both in terms of effort and time needed.
The following topics are discussed: computervision; illumination and appearance-based matching; tracking; shape recognition; image segmentation; medical image analysis; 3D reconstruction; face recognition; motion est...
The following topics are discussed: computervision; illumination and appearance-based matching; tracking; shape recognition; image segmentation; medical image analysis; 3D reconstruction; face recognition; motion estimation; illumination and image restoration; fingerprint recognition; image registration; image retrieval; and reflectance model.
In this paper we present and start analyzing the iCub World data-set, an object recognition data-set, we acquired using a Human-Robot Interaction (HRI) scheme and the iCub humanoid robot platform. Our set up allows fo...
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ISBN:
(纸本)9780769549903
In this paper we present and start analyzing the iCub World data-set, an object recognition data-set, we acquired using a Human-Robot Interaction (HRI) scheme and the iCub humanoid robot platform. Our set up allows for rapid acquisition and annotation of data with corresponding ground truth. While more constrained in its scopes - the iCub world is essentially a robotics research lab - we demonstrate how the proposed data-set poses challenges to current recognition systems. The iCubWorld data-set is publicly available (1).
We have been researching three dimensional (3D) ground-truth systems for performance evaluation of vision and perception systems in the fields of smart manufacturing and robot safety. In this paper we first present an...
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ISBN:
(纸本)9780769549903
We have been researching three dimensional (3D) ground-truth systems for performance evaluation of vision and perception systems in the fields of smart manufacturing and robot safety. In this paper we first present an overview of different systems that have been used to provide ground-truth (GT) measurements and then we discuss the advantages of physically-sensed ground-truth systems for our applications. Then we discuss in detail the three ground- truth systems that we have used in our experiments: ultra wide-band, indoor GPS, and a camera-based motion capture system. Finally, we discuss three different perception-evaluation experiments where we have used these GT systems
With the recent advances of Convolutional Neural Networks (CNN) in computervision, there have been rapid progresses in extracting roads and other features from satellite imagery for mapping and other purposes. In thi...
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ISBN:
(数字)9781538661000
ISBN:
(纸本)9781538661000
With the recent advances of Convolutional Neural Networks (CNN) in computervision, there have been rapid progresses in extracting roads and other features from satellite imagery for mapping and other purposes. In this paper, we propose a new method for road extraction using stacked U-Nets with multiple output. A hybrid loss function is used to address the problem of unbalanced classes of training data. Post-processing methods, including road map vectorization and shortest path search with hierarchical thresholds, help improve recall. The overall improvement of mean IoU compared to the vanilla VGG network is more than 20%.
Live demonstration setup. (Left) The setup consists of a DAVIS346B event camera connected to a standard consumer laptop and undergoes some motion. (Right) The motion estimates are plotted in red and, for rotation-like...
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ISBN:
(纸本)9781665448994
Live demonstration setup. (Left) The setup consists of a DAVIS346B event camera connected to a standard consumer laptop and undergoes some motion. (Right) The motion estimates are plotted in red and, for rotation-like motions, the angular velocities provided by the camera IMU are also plotted in blue. This plot exemplifies an event camera undergoing large rotational motions (up to ~ 1000 deg/s) around the (a) x-axis, (b) y-axis and (c) z-axis. Overall, the incremental motion estimation method follows the IMU measurements. Optionally, the resultant global optical flow can also be shown, as well as the corresponding generated events by accumulating them onto the image plane (bottom left corner).
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