This paper proposes an efficient method to improve image quality based on Context-based enhancement techniques, particularly towards real-time applications in dedicated hardware systems. The main idea is that all the ...
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In this paper, we present a novel algorithm for reliable and fast feature matching. Inspired by recent efforts in optimizing the matching process using geometric and statistical properties, we developed an approach wh...
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ISBN:
(纸本)9783319464787;9783319464770
In this paper, we present a novel algorithm for reliable and fast feature matching. Inspired by recent efforts in optimizing the matching process using geometric and statistical properties, we developed an approach which constrains the search space by utilizing spatial statistics from a small subset of matched and filtered correspondences. We call this method Guided Matching based on Statistical Optical Flow (GMbSOF). To ensure broad applicability, our approach works on high dimensional descriptors like SIFT but also on binary descriptors like FREAK. To evaluate our algorithm, we developed a novel method for determining ground truth matches, including true negatives, using spatial ground truth information of well known datasets. Therefore, we evaluate not only with precision and recall but also with accuracy and fall-out. We compare our approach in detail to several relevant state-of-the-art algorithms using these metrics. Our experiments show that our method outperforms all other tested solutions in terms of processing time while retaining a comparable level of matching quality.
This document describes a demonstration, proposed at DASIP Demo Night session. This demonstration is running on a low-power manycore processor from Kalray, named MPPA ® and is highlighting capabilities of this n...
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This document describes a demonstration, proposed at DASIP Demo Night session. This demonstration is running on a low-power manycore processor from Kalray, named MPPA ® and is highlighting capabilities of this new generation chip in processing multiple applications.
Unauthorized and unregistered sea going fishing vessels are being used for criminal activities in the coastal areas. The issue of piracy against merchant ships using illegal fishing vessels poses a significant threat ...
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ISBN:
(纸本)9781467393379
Unauthorized and unregistered sea going fishing vessels are being used for criminal activities in the coastal areas. The issue of piracy against merchant ships using illegal fishing vessels poses a significant threat to world shipping. Unfortunately counter piracy efforts and maritime security of our own and other nation enforcement often affects the innocent fishermen who conduct the trans-border fishing. Hence a proper vessel monitoring system is required to protect the maritime security without tampering the routine fishing activity of the sea going fishermen. This paper discusses about the feasibility of a system for the detection of registered marine fishing vessels comparing the satellite images and GPRS signal information. A review on various algorithms for identifying marine boats from satellite images is also conducted in this paper.
This paper describes the optical setup and imageprocessing required to estimate melt-pool width and build height for real-time control of melt-pool geometry in directed energy deposition additive manufacturing. To ov...
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The proceedings contain 30 papers. The topics discussed include: defect automatic detection for tire x-ray images using inverse transformation of principal component residual;co-channel interference mitigation on capa...
ISBN:
(纸本)9781467391870
The proceedings contain 30 papers. The topics discussed include: defect automatic detection for tire x-ray images using inverse transformation of principal component residual;co-channel interference mitigation on capacity and coverage in cellular systems;dyadic lifting wavelet based signal detection;multi-view matching points extraction algorithm based on union find sets;revocation basis and proofs access control for cloud storage multi-authority systems;a detection method for network security based on the combination of support vector machine;issues on critical objects in mining algorithms;motion background modeling based on context-encoder;application of intelligence of swarm in architecture;features selection for building an early diagnosis machine learning model for Parkinson's disease;latent fingerprint wavelet transform image enhancement technique for optical coherence tomography;synchronizing switching times of vacuum interrupters for medium voltage switchboards' techniques;performance analysis of the method for social search of information in university information systems;and modeling and data processing of information systems.
Automatic face recognition technologies have seen significant improvements in performance due to a combination of advances in deep learning and availability of larger datasets for training deep networks. Since recogni...
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ISBN:
(纸本)9781509014378
Automatic face recognition technologies have seen significant improvements in performance due to a combination of advances in deep learning and availability of larger datasets for training deep networks. Since recognizing faces is a task that humans are believed to be very good at, it is only natural to compare the relative performance of automated face recognition and humans when processing fully unconstrained facial imagery. In this work, we expand on previous studies of the recognition accuracy of humans and automated systems by performing several novel analyses utilizing unconstrained face imagery. We examine the impact on performance when human recognizers are presented with varying amounts of imagery per subject, immutable attributes such as gender, and circumstantial attributes such as occlusion, illumination, and pose. Results indicate that humans greatly outperform state of the art automated face recognition algorithms on the challenging IJB-A dataset.
Registration plate recognition plays a vital role in numerous applications in today’s world. We also introduce a new approach using genetic algorithm to figure out the registration plate location. Fluctuating illumin...
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It is well known that automatic speaker verification (ASV) systems can be vulnerable to spoofing. The community has responded to the threat by developing dedicated countermeasures aimed at detecting spoofing attacks. ...
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ISBN:
(纸本)9781510833135
It is well known that automatic speaker verification (ASV) systems can be vulnerable to spoofing. The community has responded to the threat by developing dedicated countermeasures aimed at detecting spoofing attacks. Progress in this area has accelerated over recent years, partly as a result of the first standard evaluation, ASVspoof 2015, which focused on spoofing detection in isolation from ASV. This paper investigates the integration of state-of-the-art spoofing countermeasures in combination with ASV. Two general strategies to countermeasure integration are reported: cascaded and parallel. The paper reports the first comparative evaluation of each approach performed with the ASVspoof 2015 corpus. Results indicate that, even in the case of varying spoofing attack algorithms, ASV performance remains robust when protected with a diverse set of integrated countermeasures.
In this paper, we propose a relocalization method for keyframe-based SLAM that enables real-time and accurate recovery from tracking failures. To realize an AR-based application in a real world situation, not only acc...
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ISBN:
(纸本)9781509008360
In this paper, we propose a relocalization method for keyframe-based SLAM that enables real-time and accurate recovery from tracking failures. To realize an AR-based application in a real world situation, not only accurate camera tracking but also fast and accurate relocalization from tracking failure is required. The previous keyframe-based relocalization methods have some drawbacks with regard to speed and accuracy. The proposed relocalization method selects two algorithms adaptively depending on the relative camera pose between a current frame and a target keyframe. In addition, it estimates a degree of false matches to speed up RANSAC-based model estimation. We present effectiveness of our method by an evaluation using public tracking dataset.
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