Matching algorithm performance analysis for autocalibration method of stereo vision

Stereo vision is one of the interesting research topics in the computer vision field. Two cameras are used to generate a disparity map, resulting in the depth estimation. Camera calibration is the most important step in stereo vision. The calibration step is used to generate an intrinsic parameter of each camera to get a better disparity map. In general, the calibration process is done manually by using a chessboard pattern, but this process is an exhausting task. Self-calibration is an important ability required to overcome this problem. Self-calibration required a robust and good matching algorithm to find the key feature between images as reference. The purpose of this paper is to analyze the performance of three matching algorithms for the autocalibration process. The matching algorithms used in this research are SIFT, SURF, and ORB. The result shows that SIFT performs better than other methods

Spatial registration of neuron morphologies based on maximization of volume overlap

Background: Morphological features are widely used in the study of neuronal function and pathology. Invertebrate neurons are often structurally stereotypical, showing little variance in gross spatial features but larger variance in their fine features. Such variability can be quantified using detailed spatial analysis, which however requires the morphologies to be registered to a common frame of reference. Results: We outline here new algorithms - Reg-MaxS and Reg-MaxS-N - for co-registering pairs and groups of morphologies, respectively. Reg-MaxS applies a sequence of translation, rotation and scaling transformations, estimating at each step the transformation parameters that maximize spatial overlap between the volumes occupied by the morphologies. We test this algorithm with synthetic morphologies, showing that it can account for a wide range of transformation differences and is robust to noise. Reg-MaxS-N co-registers groups of more than two morphologies by iteratively calculating an average volume and registering all morphologies to this average using Reg-MaxS. We test Reg-MaxS-N using five groups of morphologies from the Droshophila melanogaster brain and identify the cases for which it outperforms existing algorithms and produce morphologies very similar to those obtained from registration to a standard brain atlas. Conclusions: We have described and tested algorithms for co-registering pairs and groups of neuron morphologies. We have demonstrated their application to spatial comparison of stereotypic morphologies and calculation of dendritic density profiles, showing how our algorithms for registering neuron morphologies can enable new approaches in comparative morphological analyses and visualization

Analysis and network simulations of honeybee interneurons responsive to waggle dance vibration signals

BACKGROUND: Honeybees have long fascinated neuroscientists with their highly evolved social structure and rich behavioral repertoire. They sense air vibrations with their antennae, which is vital for several activities during foraging, like waggle dance communication and flight. GOALS: This thesis presents the investigation of the function of an identified vibration-sensitive interneuron, DL-Int-1. Primary goals were the investigation of (i) adaptations during maturation and (ii) the role of DL-Int-1 in networks encoding distance information of waggle dance vibration signals. RESULTS: Visual inspection indicated that DL-Int-1 morphologies had similar gross structure, but were translated, rotated and scaled relative to each other. To enable detailed spatial comparison, an algorithm for the spatial co-registration of neuron morphologies, Reg-MaxS-N was developed and validated. Experimental data from DL-Int-1 was provided by our Japanese collaborators. Comparison of morphologies from newly emerged adult and forager DL-Int-1 revealed minor changes in gross dendritic features and consistent, region-dependent and spatially localized changes in dendritic density. Comparison of electrophysiological response properties showed an increase in firing rate differences between stimulus and non-stimulus periods during maturation. A putative disinhibitory network in the honeybee primary auditory center was proposed based on experimental evidence. Simulations showed that the network was consistent with experimental observations and clarified the central inhibitory role of DL-Int-1 in shaping the network output. RELEVANCE: Reg-MaxS-N presents a novel approach for the spatial co-registration of morphologies. Adaptations in DL-Int-1 morphology during maturation indicate improved connectivity and signal propagation. The central role of DL-Int-1 in a disinhibitory network in the honeybee primary auditory center combined with adaptions in its response properties during maturation could indicate better encoding of distance information from waggle dance vibration sig- nals

A Methodology to Develop Computer Vision Systems in Civil Engineering: Applications in Material Testing and Fish Tracking

[Resumen] La Visión Artificial proporciona una nueva y prometedora aproximación al campo de la Ingeniería Civil, donde es extremadamente importante medir con precisión diferentes procesos. Sin embargo, la Visión Artificial es un campo muy amplio que abarca multitud de técnicas y objetivos, y definir una aproximación de desarrollo sistemática es problemático. En esta tesis se propone una nueva metodología para desarrollar estos sistemas considerando las características y requisitos de la Ingeniería Civil. Siguiendo esta metodología se han desarrollado dos sistemas: Un sistema para la medición de desplazamientos y deformaciones en imágenes de ensayos de resistencia de materiales. Solucionando las limitaciones de los actuales sensores físicos que interfieren con el ensayo y solo proporcionan mediciones en un punto y una dirección determinada. Un sistema para la medición de la trayectoria de peces en escalas de hendidura vertical, con el que se pretende solucionar las carencias en el diseño de escalas obteniendo información sobre el comportamiento de los peces. Estas aplicaciones representan contribuciones significativas en el área, y demuestran que la metodología definida e implementada proporciona un marco de trabajo sistemático y confiable para el desarrollo de sistemas de Visión Artificial en Ingeniería Civil.[Resumo] A Visión Artificial proporciona unha nova e prometedora aproximación ó campo da Enxeñería Civil, onde é extremadamente importante medir con precisión diferentes procesos. Sen embargo, a Visión Artificial é un campo moi amplo que abarca multitude de técnicas e obxectivos, e definir unha aproximación de desenvolvemento sistemática é problemático. En esta tese proponse unha nova metodoloxía para desenvolver estes sistemas considerando as características e requisitos da Enxeñería Civil. Seguindo esta metodoloxía desenvolvéronse dous sistemas: Un sistema para a medición de desprazamentos e deformacións en imaxes de ensaios de resistencia de materiais. Solucionando as limitacións dos actuais sensores físicos que interfiren co ensaio e só proporcionan medicións nun punto e nunha dirección determinada. Un sistema para a medición da traxectoria de peixes en escalas de fenda vertical, co que se pretende solucionar as carencias no deseño de escalas obtendo información sobre o comportamento dos peixes. Estas aplicacións representan contribucións significativas na área, e demostran que a metodoloxía definida e implementada proporciona un marco de traballo sistemático e confiable para o desenvolvemento de sistemas de Visión Artificial en Enxeñería Civil.[Abstract] Computer Vision provides a new and promising approach to Civil Engineering, where it is extremely important to measure with accuracy real world processes. However, Computer Vision is a broad field, involving several techniques and topics, and the task of defining a systematic development approach is problematic. In this thesis a new methodology is carried out to develop these systems attending to the special characteristics and requirements of Civil Engineering. Following this methodology, two systems were developed: A system to measure displacements from real images of material surfaces taken during strength tests. This technique solves the limitation of current physical sensors, which interfere with the assay and which are limited to obtaining measurements in a single point of the material and in a single direction of the movement. A system to measure the trajectory of fishes in vertical slot fishways, whose purpose is to solve current lacks in the design of fishways by providing information of fish behavior. These applications represent significant contributions to the field and show that the defined and implemented methodology provides a systematic and reliable framework to develop a Computer Vision system in Civil Engineering