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.
image segmentation is a key component in many computer vision systems, and it is recovering a prominent spot in the literature as methods improve and overcome their limitations. The outputs of most recent algorithms a...
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ISBN:
(纸本)9781467388511
image segmentation is a key component in many computer vision systems, and it is recovering a prominent spot in the literature as methods improve and overcome their limitations. The outputs of most recent algorithms are in the form of a hierarchical segmentation, which provides segmentation at different scales in a single tree-like structure. Commonly, these hierarchical methods start from some lowlevel features, and are not aware of the scale information of the different regions in them. As such, one might need to work on many different levels of the hierarchy to find the objects in the scene. This work tries to modify the existing hierarchical algorithm by improving their alignment, that is, by trying to modify the depth of the regions in the tree to better couple depth and scale. To do so, we first train a regressor to predict the scale of regions using mid-level features. We then define the anchor slice as the set of regions that better balance between over-segmentation and undersegmentation. The output of our method is an improved hierarchy, re-aligned by the anchor slice. To demonstrate the power of our method, we perform comprehensive experiments, which show that our method, as a post-processing step, can significantly improve the quality of the hierarchical segmentation representations, and ease the usage of hierarchical image segmentation to high-level vision tasks such as object segmentation. We also prove that the improvement generalizes well across different algorithms and datasets, with a low computational cost.1.
Three-dimensional cone-beam (CB) imaging using a multi-axis floor-mounted (or ceiling-mounted) C-arm system has become an important tool in interventional radiology. This success motivates new developments to improve ...
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ISBN:
(纸本)9781510600188
Three-dimensional cone-beam (CB) imaging using a multi-axis floor-mounted (or ceiling-mounted) C-arm system has become an important tool in interventional radiology. This success motivates new developments to improve image quality. One direction in which advancement is sought is the data acquisition geometry and related CB artifacts. Currently, data acquisition is performed using the circular short-scan trajectory, which yields limited axial coverage and also provides incomplete data for accurate reconstruction. To improve the image quality, as well as to increase the coverage in the longitudinal direction of the patient, we recently introduced the ellipse line -ellipse trajectory and showed that this trajectory provides full R-line coverage within the field-of-view, which is a key property for accurate reconstruction from truncated data. An R-line is any segment of line that connects two source positions. Here, we examine how the application of asymmetrical variations to the definition of the ELE trajectory impacts the R-line coverage. This question is significant to understand how much flexibility can be used in the implementation of the ELE trajectory, particularly to adapt the scan to patient anatomy and imaging task of interest. Two types of asymmetrical variations, called axial and angular variations, are investigated.
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