Over the decade scientists have been researching to know whether face recognition is performed holistically or with local feature analysis which has led to the proposition of various advanced methods in face recogniti...
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ISBN:
(纸本)9781728107844
Over the decade scientists have been researching to know whether face recognition is performed holistically or with local feature analysis which has led to the proposition of various advanced methods in face recognition, especially using facial landmark. The current facial landmark methods in 3D are mathematically complex, contain insufficient landmarks, lack homology and full of localization error due to manual annotation. This paper proposes an Automatic Homologous Multi-Points Warping (AHMW) for 3D facial landmarking, experimented on three datasets using 500 landmarks (16 anatomical fixed points and 484 sliding semi-landmarks) by building a template mesh as a reference object and thereby applies the template to each of the targets on three datasets. The results show that the method is robust with minimum localization error (Stirling/ESRC:0.077;Bosphorus:0.088;and FRGC v2: 0.083).
Over the years, neuroscientists and psychophysicists have been asking whether data acquisition for facial analysis should be performed holistically or with local feature analysis. This has led to various advanced meth...
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Over the years, neuroscientists and psychophysicists have been asking whether data acquisition for facial analysis should be performed holistically or with local feature analysis. This has led to various advanced methods of face recognition being proposed, and especially techniques using facial landmarks. The current facial landmark methods in 3D involve a mathematically complex and time-consuming workflow involving semi-landmark sliding tasks. This paper proposes a homologous multi-point warping for 3D facial landmarking, which is verified experimentally on each of the target objects in a given dataset using 500 landmarks (16 anatomical fixed points and 484 sliding semi-landmarks). This is achieved by building a template mesh as a reference object and applying this template to each of the targets in three datasets using an artificial deformation approach. The semi-landmarks are subjected to sliding along tangents to the curves or surfaces until the bending energy between a template and a target form is minimal. The results indicate that our method can be used to investigate shape variation for multiple datasets when implemented on three databases (Stirling, FRGC and Bosphorus).
Due to the evolution of information technology, it is becoming increasingly easy to use new platforms in order to set up efficient systems that are well adapted to the expected needs. As part of improving security and...
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ISBN:
(纸本)9781728175133
Due to the evolution of information technology, it is becoming increasingly easy to use new platforms in order to set up efficient systems that are well adapted to the expected needs. As part of improving security and facilitating the detection of potentially dangerous persons, an intelligent application for on-board facial recognition is being developed. It is within this framework that we propose this paper. The objective of the proposed work is twofold. On the one hand, we propose to develop a module for the detection of relevant facial characteristics, which is the first step of an intelligent video surveillance application. Based on the detection of points of interest of the landmark algorithm, a software optimization of the work is proposed. On the other hand, this application will be decomposed in order to be embedded on a multiprocessor architecture. In order to validate the multiprocessor-based approach, a comparison with other existing powerful processor architectures will allow to validate the best approach. This work will be the input for an intelligent embedded face detection application based on Machine Learning.
In view of the problem that the existing RFID based roadmap (LANDMARC) indoor positioning system will lead to the loss of good adjacent reference labels and the introduction of bad reference labels due to external env...
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In view of the problem that the existing RFID based roadmap (LANDMARC) indoor positioning system will lead to the loss of good adjacent reference labels and the introduction of bad reference labels due to external environment factors, a RFID location algorithm based on reference label is proposed. Several reference labels are taken as a whole to compare the value of Receive Signal Strength Indicator (RSSI) to the location label. First, find the area range of the location label, and add some reference labels in this area, and finally determine the position coordinates of the fixed label by adding weight estimation. The experimental results show that the improved algorithm has better stability and anti-interference without increasing the cost of any hardware, and can effectively obtain a good reference label, thus obtaining satisfactory positioning accuracy and positioning performance.
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