Accuracy estimation of a new omnidirectional 3D vision sensor

We present a computer vision system that associates omnidirectional vision with structured light with the aim of obtaining depth information for a 360 degrees field of view. The approach proposed in this article combines an omnidirectional camera with a panoramic laser projector. The article shows how the sensor is modelled and its accuracy is proved by means of experimental results. The proposed sensor provides useful information for robot navigation applications, pipe inspection, 3D scene modelling etc

Omnidirectional Depth Computation from a Single Image

Omnidirectional cameras offer a much wider field of view than the perspective ones and alleviate the problems due to occlusions. However, both types of cameras suffer from the lack of depth perception. A practical method for obtaining depth in computer vision is to project a known structured light pattern on the scene avoiding the problems and costs involved by stereo vision. This paper is focused on the idea of combining omnidirectional vision and structured light with the aim to provide 3D information about the scene. The resulting sensor is formed by a single catadioptric camera and an omnidirectional light projector. It is also discussed how this sensor can be used in robot navigation applications

Calibration of a Structured Light-Based Stereo Catadioptric Sensor

Catadioptric sensors are combinations of mirrors and lenses made in order to obtain a wide field of view. In this paper we propose a new sensor that has omnidirectional viewing ability and it also provides depth information about the nearby surrounding. The sensor is based on a conventional camera coupled with a laser emitter and two hyperbolic mirrors. Mathematical formulation and precise specifications of the intrinsic and extrinsic parameters of the sensor are discussed. Our approach overcomes limitations of the existing omni-directional sensors and eventually leads to reduced costs of production

A Camera-Projector System for Robot Positioning by Visual Servoing

Positioning a robot with respect to objects by using data provided by a camera is a well known technique called visual servoing. In order to perform a task, the object must exhibit visual features which can be extracted from different points of view. Then, visual servoing is object-dependent as it depends on the object appearance. Therefore, performing the positioning task is not possible in presence of nontextured objets or objets for which extracting visual features is too complex or too costly. This paper proposes a solution to tackle this limitation inherent to the current visual servoing techniques. Our proposal is based on the coded structured light approach as a reliable and fast way to solve the correspondence problem. In this case, a coded light pattern is projected providing robust visual features independently of the object appearance

La Cantata a Europa a l’entorn del segle XVIII : música da camera italiana del Barroc tardà

La cantata da camera italiana va tenir el seu màxim esplendor durant el segle XVII i principis del XVIII. A partir de l’anàlisi d’obres de quatre compositors (Albinoni, Scarlatti, Caldara i Vivaldi) s’estudia l’evolució d’aquesta forma, els seus orígens i la seva interpretació, fent especial atenció al text i a l’ornamentació.

Versatile iPad forensic acquisition using the Apple Camera Connection Kit

Peer reviewed

An embedded real-time red peach detection system based on an OV7670 camera, ARM Cortex-M4 processor and 3D Look-Up Tables

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

Identification of Paintings from Camera-Phone Images

Peer-reviewed

Identification of paintings from camera-phone images

Peer-reviewed

Disseny i implementació hardware d'algorismes de reconeixement de caràcters per comptadors d'aigua

Aquest projecte consisteix en l'estudi, comparació i implementació en hardware d'algoritmes de reconeixement de caràcters per integrar en un sistema intel·ligent de captura d'imatges. Aquest sistema, integrat per una càmera amb format i característiques específiques i que anirà acoblat a un comptador d'aigua tradicional, en captarà imatges i les enviarà per RF al punt de recepció de la companyia. L'objectiu principal consisteix en aconseguir un disseny que redueixi al màxim la quantitat d'informació per transmetre, tenint en compte les limitacions de l'entorn.

Testing low-altitude infrared digital photography from a mini-UAV to retrieve information for biological conservation

Satellite remote sensing imagery is used for forestry, conservation and environmental applications, but insufficient spatial resolution, and, in particular, unavailability of images at the precise timing required for a given application, often prevent achieving a fully operational stage. Airborne remote sensing has the advantage of custom-tuned sensors, resolution and timing, but its price prevents using it as a routine technique for the mentioned fields. Some Unmanned Aerial Vehicles might provide a “third way” solution as low-cost techniques for acquiring remotely sensed information, under close control of the end-user, albeit at the expense of lower quality instrumentation and instability. This report evaluates a light remote sensing system based on a remotely-controlled mini-UAV (ATMOS-3) equipped with a color infra-red camera (VEGCAM-1) designed and operated by CATUAV. We conducted a testing mission over a Mediterranean landscape dominated by an evergreen woodland of Aleppo pine (Pinus halepensis) and (Holm) oak (Quercus ilex) in the Montseny National Park (Catalonia, NE Spain). We took advantage of state-of-the-art ortho-rectified digital aerial imagery (acquired by the Institut Cartogràfic de Catalunya over the area during the previous year) and used it as quality reference. In particular, we paid attention to: 1) Operationality of flight and image acquisition according to a previously defined plan; 2) Radiometric and geometric quality of the images; and 3) Operational use of the images in the context of applications. We conclude that the system has achieved an operational stage regarding flight activities, although with meteorological limits set by wind speed and turbulence. Appropriate landing areas can be sometimes limiting also, but the system is able to land on small and relatively rough terrains such as patches of grassland or short matorral, and we have operated the UAV as far as 7 km from the control unit. Radiometric quality is sufficient for interactive analysis, but probably insufficient for automated processing. A forthcoming camera is supposed to greatly improve radiometric quality and consistency. Conventional GPS positioning through time synchronization provides coarse orientation of the images, with no roll information.

Intestinal content detection in capsule endoscopy using robust features

This work covers two aspects. First, it generally compares and summarizes the similarities and differences of state of the art feature detector and descriptor and second it presents a novel approach of detecting intestinal content (in particular bubbles) in capsule endoscopy images. Feature detectors and descriptors providing invariance to change of perspective, scale, signal-noise-ratio and lighting conditions are important and interesting topics in current research and the number of possible applications seems to be numberless. After analysing a selection of in the literature presented approaches, this work investigates in their suitability for applications information extraction in capsule endoscopy images. Eventually, a very good performing detector of intestinal content in capsule endoscopy images is presented. A accurate detection of intestinal content is crucial for all kinds of machine learning approaches and other analysis on capsule endoscopy studies because they occlude the field of view of the capsule camera and therefore those frames need to be excluded from analysis. As a so called “byproduct” of this investigation a graphical user interface supported Feature Analysis Tool is presented to execute and compare the discussed feature detectors and descriptor on arbitrary images, with configurable parameters and visualized their output. As well the presented bubble classifier is part of this tool and if a ground truth is available (or can also be generated using this tool) a detailed visualization of the validation result will be performed.

Plataforma de adquisición de imágenes en escenarios virtuales para uso en sistemas de visión

En aquest projecte presentem un mètode per generar bases de imatges de vianants, requerides per a l'entrenament o validació de sistemes d'aprenentatge basats en exemples, en un entorn virtual. S'ha desenvolupat una plataforma que permet simular una navegació d'una càmara en una escena virtual i recuperar el fluxe de vídeo amb el seu groundtruth. Amb l'ús d'aquesta plataforma es suprimeix el procés d'anotació, necesari per obtenir el groundtruth en entorns reals, i es redueixen els costos al treballar en un entorn virtual.

Ayuda para la configuración de cámaras

Este proyecto está destinado a proporcionar herramientas que ayuden en la configuración de cámaras para uso industrial pero también se pueden exportar a otros campos relacionados con el vídeo y la fotografía digital. Las herramientas desarrolladas ayudan a la configuración del balance de blancos, el grado de exposición al que está sometida la escena capturada por la cámara y a calcular el mejor enfoque posible. Además, se ha desarrollado una herramienta que permita al usuario una configuración más cómoda de los parámetros de la cámara. Estos módulos se han desarrollado sobre el software VisionOkII.

Underwater Gigamosaicing

El procés de fusió de dues o més imatges de la mateixa escena en una d'única i més gran és conegut com a Image Mosaicing. Un cop finalitzat el procés de construcció d'un mosaic, els límits entre les imatges són habitualment visibles, degut a imprecisions en els registres fotomètric i geomètric. L'Image Blending és l'etapa del procediment de mosaicing a la que aquests artefactes són minimitzats o suprimits. Existeixen diverses metodologies a la literatura que tracten aquests problemes, però la majoria es troben orientades a la creació de panorames terrestres, imatges artístiques d'alta resolució o altres aplicacions a les quals el posicionament de la càmera o l'adquisició de les imatges no són etapes rellevants. El treball amb imatges subaquàtiques presenta desafiaments importants, degut a la presència d'scattering (reflexions de partícules en suspensió) i atenuació de la llum i a condicions físiques extremes a milers de metres de profunditat, amb control limitat dels sistemes d'adquisició i la utilització de tecnologia d'alt cost. Imatges amb il·luminació artificial similar, sense llum global com la oferta pel sol, han de ser unides sense mostrar una unió perceptible. Les imatges adquirides a gran profunditat presenten una qualitat altament depenent de la profunditat, i la seva degradació amb aquest factor és molt rellevant. El principal objectiu del treball és presentar dels principals problemes de la imatge subaquàtica, seleccionar les estratègies més adequades i tractar tota la seqüència adquisició-procesament-visualització del procés. Els resultats obtinguts demostren que la solució desenvolupada, basada en una Estratègia de Selecció de Límit Òptim, Fusió en el Domini del Gradient a les regions comunes i Emfatització Adaptativa d'Imatges amb baix nivell de detall permet obtenir uns resultats amb una alta qualitat. També s'ha proposat una estratègia, amb possibilitat d'implementació paral·lela, que permet processar mosaics de kilòmetres d'extensió amb resolució de centímetres per píxel.