922 resultados para Biometric Descriptor
Resumo:
En este trabajo se propone un método que combina descriptores de imágenes de intensidad y de profundidad para detectar de manera robusta el problema de cierre de bucle en SLAM. La robustez del método, proporcionada por el empleo conjunto de información de diversa naturaleza, permite detectar lugares revisitados en situaciones donde m´etodos basados solo en intensidad o en profundidad presentan dificultades (p.e. condiciones de iluminación deficientes, o falta de geometría). Además, se ha diseñado el métod cuenta su eficiencia, recurriendo para ello al detector FAST para extraer las características de las observaciones y al descriptor binario BRIEF. La detección de bucle se completa con una Bolsa de Palabras binarias. El rendimiento del método propuesto se ha evaluado en condiciones reales, obteniéndose resultados muy satisfactorios.
Resumo:
Ecomorphology is a science based on the idea that morphological differences among species could be associated with distinct biological and environmental pressures suffered by them. These differences can be studied employing morphological and biometric indexes denominated Ecomorphological attributes , representing standards that express characteristics of the individual in relation to its environment, and can be interpreted as indicators of life habits or adaptations suffered due its occupation of different habitats. This work aims to contribute for the knowledge of the ecomorphology of the Brazilian marine ichthyofauna, specifically from Galinhos, located at Rio Grande do Norte state. 10 different species of fish were studied, belonging the families Gerreidae (Eucinostomus argenteus), Haemulidae (Orthopristis ruber,Pomadasyscorvinaeformis,Haemulonaurolineatum,Haemulonplumieri,Haemulonsteindachneri), Lutjanidae (Lutjanus synagris), Paralichthyidae (Syaciummicrurum), Bothidae (Bothus ocellatus) and Tetraodontidae (Sphoeroidestestudineus), which were obtained during five collections, in the period time of September/2004 to April/2005, utilizing three special nets. The ecomorphological study was performed at the laboratory. Eight to ten samples of each fish specie were measured. Fifteen morphological aspects were considered to calculate twelve ecomorphological attributes. Multivariate statistical analysis methods such as Principal Component Analysis (PCA) and Cluster Analysis were done to identify ecmorphological patterns to describe the data set obtained. As results, H.aurolineatumwas the most abundant specie found (23,03%) and S.testudineusthe less one with 0,23%. The 1st Principal component showed variation of 60,03% with influence of the ecomorphological attribute related to body morphology, while the 2nd PC with 23,25% variation had influence of the ecomorphological attribute related to oral morphology. The Cluster Analiysis promoted the identification of three distinct groups Perciformes, Pleuronectiformes and Tetraodontiformes. Based on the obtained data, considering morphological characters differences among the species studied, we suggest that all of them live at the medium (E.argenteus,O.rubber, P.corvinaeformis,H.aurolineatum,H.plumieri,H.steindachneri,L.synagris) and bottom (S.micrurum,B.ocellatus,S.testudineus) region of column water.
Resumo:
Human scent, or the volatile organic compounds (VOCs) produced by an individual, has been recognized as a biometric measurement because of the distinct variations in both the presence and abundance of these VOCs between individuals. In forensic science, human scent has been used as a form of associative evidence by linking a suspect to a scene/object through the use of human scent discriminating canines. The scent most often collected and used with these specially trained canines is from the hands because a majority of the evidence collected is likely to have been handled by the suspect. However, the scents from other biological specimens, especially those that are likely to be present at scenes of violent crimes, have yet to be explored. Hair, fingernails and saliva are examples of these types of specimens. In this work, a headspace solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) technique was used for the identification of VOCs from hand odor, hair, fingernails and saliva. Sixty individuals were sampled and the profiles of the extracted VOCs were evaluated to assess whether they could be used for distinguishing individuals. Preliminary analysis of the biological specimens collected from an individual (intra-subject) showed that, though these materials have some VOCs in common, their overall chemical profile is different for each specimen type. Pair-wise comparisons, using Spearman Rank correlations, were made between the chemical profiles obtained from each subject, per a specimen type. Greater than 98.8% of the collected samples were distinguished from the subjects for all of the specimen types, demonstrating that these specimens can be used for distinguishing individuals. Additionally, field trials were performed to determine the utility of these specimens as scent sources for human scent discriminating canines. Three trials were conducted to evaluate hair, fingernails and saliva in comparison to hand odor, which was considered the standard source of human odor. It was revealed that canines perform similarly to these alternative human scent sources as they do to hand odor implying that, though there are differences in the chemical profiles released by these specimens, they can still be used for the discrimination of individuals by trained canines.
Resumo:
Laplacian-based descriptors, such as the Heat Kernel Signature and the Wave Kernel Signature, allow one to embed the vertices of a graph onto a vectorial space, and have been successfully used to find the optimal matching between a pair of input graphs. While the HKS uses a heat di↵usion process to probe the local structure of a graph, the WKS attempts to do the same through wave propagation. In this paper, we propose an alternative structural descriptor that is based on continuoustime quantum walks. More specifically, we characterise the structure of a graph using its average mixing matrix. The average mixing matrix is a doubly-stochastic matrix that encodes the time-averaged behaviour of a continuous-time quantum walk on the graph. We propose to use the rows of the average mixing matrix for increasing stopping times to develop a novel signature, the Average Mixing Matrix Signature (AMMS). We perform an extensive range of experiments and we show that the proposed signature is robust under structural perturbations of the original graphs and it outperforms both the HKS and WKS when used as a node descriptor in a graph matching task.
Resumo:
Purpose: The primary outcome of this study is to compare the axial length growth of white European myopic children wearing orthokeratology contact lenses (OK) to a control group (CT) over a 7-year period. Methods: Subjects 6–12 years of age with myopia −0.75 to −4.00DS and astigmatism ≤1.00DC were prospectively allocated OK or distance single-vision spectacles (SV) correction. Measurements of axial length (Zeiss IOLMaster), corneal topography, and cycloplegic refraction were taken at 6-month intervals over a 2-year period. Subjects were invited to return to the clinic approximately 5 years later (i.e., 7 years after the beginning of the study) for assessment of their ocular refractive and biometric components. The CT consisted of 4 SV and 12 subjects who switched from SV to soft contact lens wear after the initial 2 years of SV lens wear. Changes in axial length relative to baseline over a 7-year period were compared between groups. Results: Fourteen and 16 subjects from the OK and CT groups, respectively, were examined 6.7 ± 0.5 years after the beginning of the study. Statistically significant changes in the axial length were found over time and between groups (both p <0.001), but not for the time*group interaction (p = 0.125). The change in the axial length for the OK group was 22% (p = 0.328), 42% (p = 0.007), 40% (p = 0.020), 41% (p = 0.013), and 33% (p = 0.062) lower than the CT group following 6, 12, 18, 24, and 84 months of lens wear, respectively. Conclusion: A trend toward a reduction in the rate of axial elongation of the order of 33% was found in the OK group in comparison to the CT group following 7 years of lens wear.
Resumo:
Purpose: to determine whether pupil dilation affects biometric measurements and intraocular lens (IOL) power calculation made using the new swept-source optical coherence tomography-based optical biometer (IOLMaster 700©; Carl Zeiss Meditec, Jena, Germany). Procedures: eighty-one eyes of 81 patients evaluated for cataract surgery were prospectively examined using the IOLMaster 700© before and after pupil dilation with tropicamide 1%. The measurements made were: axial length (AL), central corneal thickness (CCT), aqueous chamber depth (ACD), lens thickness (LT), mean keratometry (MK), white-to-white distance (WTW) and pupil diameter (PD). Holladay II and SRK/T formulas were used to calculate IOL power. Agreement between measurement modes (with and without dilation) was assessed through intraclass correlation coefficients (ICC) and Bland-Altman plots. Results: mean patient age was 75.17 ± 7.54 years (range: 57–92). Of the variables determined, CCT, ACD, LT and WTW varied significantly according to pupil dilation. Excellent intraobserver correlation was observed between measurements made before and after pupil dilation. Mean IOL power calculation using the Holladay 2 and SRK/T formulas were unmodified by pupil dilation. Conclusions: the use of pupil dilation produces statistical yet not clinically significant differences in some IOLMaster 700© measurements. However, it does not affect mean IOL power calculation.
Resumo:
This paper describes a novel algorithm for tracking the motion of the urethra from trans-perineal ultrasound. Our work is based on the structure-from-motion paradigm and therefore handles well structures with ill-defined and partially missing boundaries. The proposed approach is particularly well-suited for video sequences of low resolution and variable levels of blurriness introduced by anatomical motion of variable speed. Our tracking method identifies feature points on a frame by frame basis using the SURF detector/descriptor. Inter-frame correspondence is achieved using nearest-neighbor matching in the feature space. The motion is estimated using a non-linear bi-quadratic model, which adequately describes the deformable motion of the urethra. Experimental results are promising and show that our algorithm performs well when compared to manual tracking.