Motion blur is a common phenomenon in the presence of camera shake or object motion. In this paper, we deal withthe challenging situation of underwater imaging. Specifically, we assume a static camera looking vertica...
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ISBN:
(纸本)1595930361
Motion blur is a common phenomenon in the presence of camera shake or object motion. In this paper, we deal withthe challenging situation of underwater imaging. Specifically, we assume a static camera looking vertically down-wards at a scene but through a flowing water surface. the source of motion blur is due to the dynamic medium between the scene and the camera. Under reasonable assumptions, we establish that the motion blur induced by commonly observed fluid flows can serve as a valuable cue for inferring the underlying depth layers of the scene. We validate our approach with synthetic and real examples. Copyright 2014 ACM.
this paper presents a novel algorithm to dehaze a given hazy input image using a Multi-Stage progressive image Dehazing Network (MSDNet) architecture. the proposed multi-stage strategy framework splits the challenge o...
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In this paper, an interpretable deep-learning-based system has been proposed for facial emotion recognition. A novel approach to interpret the proposed system's results, Divide & Conquer based Shapley additive...
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Map image text segmentation has always been one of the difficult tasks because of its variety. the texts in a map may have the myriad background consists of various intensity values, different orientations, overlappin...
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Long range surveillance videos are often distorted by random perturbations of the optical pathways caused by atmospheric turbulence. While humans can easily perceive and separate the moving objects from the turbulent ...
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ISBN:
(纸本)1595930361
Long range surveillance videos are often distorted by random perturbations of the optical pathways caused by atmospheric turbulence. While humans can easily perceive and separate the moving objects from the turbulent motion, it is still a challenge for vision systems. In this paper, we present a near real-time approach to detecting moving objects in the presence of turbulence. As a first step, our method learns the dynamics of the latent turbulence and extracts an approximate foreground. Statistical analysis of the foreground object properties is used to eliminate noise due to turbulence preserving only the true moving objects. Our approach also results in a stable background with minimal turbulence. We tested our method on a wide range of scenarios corrupted by various levels of turbulence. Compared with state of the art, our results are quite promising. Copyright 2014 ACM.
2D Face recognition systems bound to fail on images with varying pose angles and occlusions. Many pose invariant methods are proposed in recent years but they are still not able to achieve very good accuracies. So in ...
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ISBN:
(纸本)1595930361
2D Face recognition systems bound to fail on images with varying pose angles and occlusions. Many pose invariant methods are proposed in recent years but they are still not able to achieve very good accuracies. So in order to achieve a better accuracy we need to extend algorithms over 3D faces. Due to the high cost involved in acquisition of 3D faces we developed our approach for low-cost and low-quality Microsoft Kinect Sensor and propose an algorithm to produce better results than existing 2D Face recognition techniques even after compromising on the quality of the images from the sensor. Our proposed algorithm is based on modified SURF descriptors on RGB images combined with various enhancements on automatically generated training images using Depth and Color images. We compare our results obtained with State Of the Art Techniques obtained on publicly available RGB-D Face databases. Our System obtained recognition rate of 98.07% on 30° CurtinFace Database, 89.28% on EURECOM Database, 98.00% on 15° Internal Database and 81.00% on 30° Internal Database.
To enhance the performance of Convolutional Neural Networks(CNNs), channel attention mechanism is widely employed in CNNs recently. Most existing channel attention mechanisms assign weights to feature maps to capture ...
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Trees are an integral part of many outdoor scenes and are rendered in a wide variety of computer applications like computer games, movies, simulations, architectural models, AR and VR. this has led to increasing deman...
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Face recognition is one of the most widely publicized feature in the devices today and hence represents an important problem that should be studied withthe utmost priority. As per the recent trends, the Convolutional...
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Tweening, also known as shape morphing, is an important concept in keyframe animation wherein an initial shape is transformed smoothly into a final shape. the huge body of existing literature in the areas of shape tra...
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