Behaviours implemented using a vision system based on coded light projection

In a search for new sensor systems and new methods for underwater vehicle positioning based on visual observation, this paper presents a computer vision system based on coded light projection. 3D information is taken from an underwater scene. This information is used to test obstacle avoidance behaviour. In addition, the main ideas for achieving stabilisation of the vehicle in front of an object are presented

An overview of the advantages and constraints of coded pattern projection techniques for autonomous navigation

The absolute necessity of obtaining 3D information of structured and unknown environments in autonomous navigation reduce considerably the set of sensors that can be used. The necessity to know, at each time, the position of the mobile robot with respect to the scene is indispensable. Furthermore, this information must be obtained in the least computing time. Stereo vision is an attractive and widely used method, but, it is rather limited to make fast 3D surface maps, due to the correspondence problem. The spatial and temporal correspondence among images can be alleviated using a method based on structured light. This relationship can be directly found codifying the projected light; then each imaged region of the projected pattern carries the needed information to solve the correspondence problem. We present the most significant techniques, used in recent years, concerning the coded structured light method

Sistema d'estereovisió amb una càmera

Els sistemes de visió estèreo es basen en la reconstrucció per triangulació a partir de dues càmeres, permetent la representació d’objectes del món real en tres dimensions. L’objectiu d’aquest projecte consisteix a dissenyar i implementar un sistema estèreo amb una sola càmera amb dos petits vidres d’alta transmissivitat davant de la lent, utilitzant la teoria clàssica desenvolupada a partir de dues càmeres. D’aquesta forma obtindrem un sistema molt més compacte que en el cas de tenir dues càmeres, que serà apte per entorns molt reduïts i per escenes molt properes

SLAM using an Imaging Sonar for Partially Structured Underwater Environments

In this paper we describe a system for underwater navigation with AUVs in partially structured environments, such as dams, ports or marine platforms. An imaging sonar is used to obtain information about the location of planar structures present in such environments. This information is incorporated into a feature-based SLAM algorithm in a two step process: (I) the full 360deg sonar scan is undistorted (to compensate for vehicle motion), thresholded and segmented to determine which measurements correspond to planar environment features and which should be ignored; and (2) SLAM proceeds once the data association is obtained: both the vehicle motion and the measurements whose correct association has been previously determined are incorporated in the SLAM algorithm. This two step delayed SLAM process allows to robustly determine the feature and vehicle locations in the presence of large amounts of spurious or unrelated measurements that might correspond to boats, rocks, etc. Preliminary experiments show the viability of the proposed approach

Underwater SLAM in a marina environment

This paper describes a navigation system for autonomous underwater vehicles (AUVs) in partially structured environments, such as dams, harbors, marinas or marine platforms. A mechanical scanning imaging sonar is used to obtain information about the location of planar structures present in such environments. A modified version of the Hough transform has been developed to extract line features, together with their uncertainty, from the continuous sonar dataflow. The information obtained is incorporated into a feature-based SLAM algorithm running an Extended Kalman Filter (EKF). Simultaneously, the AUV's position estimate is provided to the feature extraction algorithm to correct the distortions that the vehicle motion produces in the acoustic images. Experiments carried out in a marina located in the Costa Brava (Spain) with the Ictineu AUV show the viability of the proposed approach

Rank estimation of trajectory matrix in motion segmentation

A novel technique for estimating the rank of the trajectory matrix in the local subspace affinity (LSA) motion segmentation framework is presented. This new rank estimation is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built with LSA. The result is an enhanced model selection technique for trajectory matrix rank estimation by which it is possible to automate LSA, without requiring any a priori knowledge, and to improve the final segmentation

Enhanced Model Selection for motion segmentation

In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation

Object and Scene Classification: what does a Supervised Approach Provide us?

Given a set of images of scenes containing different object categories (e.g. grass, roads) our objective is to discover these objects in each image, and to use this object occurrences to perform a scene classification (e.g. beach scene, mountain scene). We achieve this by using a supervised learning algorithm able to learn with few images to facilitate the user task. We use a probabilistic model to recognise the objects and further we classify the scene based on their object occurrences. Experimental results are shown and evaluated to prove the validity of our proposal. Object recognition performance is compared to the approaches of He et al. (2004) and Marti et al. (2001) using their own datasets. Furthermore an unsupervised method is implemented in order to evaluate the advantages and disadvantages of our supervised classification approach versus an unsupervised one

Pre-procés i segmentació en imatges d’ultrasons 2D i 3D de la pròstata

Aquest projecte s'ha dut a terme amb el Grup de visió per computador del departamentd'Arquitectura i Tecnologia de Computadors (ATC) de la Universitat de Girona. Està enfocat a l'anàlisi d'imatges mèdiques, en concret s'analitzaran imatges de pròstata en relació a desenvolupaments que s'estan realitzant en el grup de visió esmentat. Els objectius fixats per aquest projecte són desenvolupar dos mòduls de processamentm d'imatges els quals afrontaran dos blocs important en el tractament d'imatges, aquests dos mòduls seran un pre-processat d'imatges, que constarà de tres filtres i un bloc de segmentació per tal de cercar la pròstata dintre de les imatges a tractar. En el projecte es treballarà amb el llenguatge de programació C++, concretament amb unes llibreries que es denominen ITK (Insight Toolkit ) i són open source enfocades al tractament d'imatges mèdiques. A part d'aquesta eina s'utilitzaran d'altres com les Qt que és una biblioteca d'eines per crear entorns gràfics

Sistema informàtic d’ajut a la detecció i al seguiment del melanoma

Mitjançant les tècniques de visió per computador aquest projecte pretén desenvolupar una aplicació capaç de segmentar la pell, detectar nevus (pigues i altres taques) i poder comparar imatges de pacients amb risc de contreure melanoma preses en moments diferents. Aquest projecte pretén oferir diferents eines informàtiques als dermatòlegs per a propòsits relacionats amb la investigació. L’ objectiu principal d’ aquest projecte és desenvolupar un sistema informàtic que proporcioni als dermatòlegs agilitat a l’hora de gestionar les dades dels pacients amb les sevesimatges corresponents, ajudar-los en la realització de deteccions dels nevus d’aquestes imatges, i ajudar-los en la comparació d’exploracions (amb les deteccions realitzades)de diferents èpoques d’un mateix pacient

A Motion compensated filtering approach to remove sunlight flicker in shallow water images

A common problem in video surveys in very shallow waters is the presence of strong light fluctuations, due to sun light refraction. Refracted sunlight casts fast moving patterns, which can significantly degrade the quality of the acquired data. Motivated by the growing need to improve the quality of shallow water imagery, we propose a method to remove sunlight patterns in video sequences. The method exploits the fact that video sequences allow several observations of the same area of the sea floor, over time. It is based on computing the image difference between a given reference frame and the temporal median of a registered set of neighboring images. A key observation is that this difference will have two components with separable spectral content. One is related to the illumination field (lower spatial frequencies) and the other to the registration error (higher frequencies). The illumination field, recovered by lowpass filtering, is used to correct the reference image. In addition to removing the sunflickering patterns, an important advantage of the approach is the ability to preserve the sharpness in corrected image, even in the presence of registration inaccuracies. The effectiveness of the method is illustrated in image sets acquired under strong camera motion containing non-rigid benthic structures. The results testify the good performance and generality of the approach

Planar homography: accuracy analysis and applications

Projective homography sits at the heart of many problems in image registration. In addition to many methods for estimating the homography parameters (R.I. Hartley and A. Zisserman, 2000), analytical expressions to assess the accuracy of the transformation parameters have been proposed (A. Criminisi et al., 1999). We show that these expressions provide less accurate bounds than those based on the earlier results of Weng et al. (1989). The discrepancy becomes more critical in applications involving the integration of frame-to-frame homographies and their uncertainties, as in the reconstruction of terrain mosaics and the camera trajectory from flyover imagery. We demonstrate these issues through selected examples

Globally aligned photomosaic of the Lucky Strike hydrothermal vent field (Mid-Atlantic Ridge, 37°18.5’N): Release of georeferenced data, mosaic construction, and viewing software

We present a georeferenced photomosaic of the Lucky Strike hydrothermal vent field (Mid-Atlantic Ridge, 37°18’N). The photomosaic was generated from digital photographs acquired using the ARGO II seafloor imaging system during the 1996 LUSTRE cruise, which surveyed a ~1 km2 zone and provided a coverage of ~20% of the seafloor. The photomosaic has a pixel resolution of 15 mm and encloses the areas with known active hydrothermal venting. The final mosaic is generated after an optimization that includes the automatic detection of the same benthic features across different images (feature-matching), followed by a global alignment of images based on the vehicle navigation. We also provide software to construct mosaics from large sets of images for which georeferencing information exists (location, attitude, and altitude per image), to visualize them, and to extract data. Georeferencing information can be provided by the raw navigation data (collected during the survey) or result from the optimization obtained from imatge matching. Mosaics based solely on navigation can be readily generated by any user but the optimization and global alignment of the mosaic requires a case-by-case approach for which no universally software is available. The Lucky Strike photomosaics (optimized and navigated-only) are publicly available through the Marine Geoscience Data System (MGDS, http://www.marine-geo.org). The mosaic-generating and viewing software is available through the Computer Vision and Robotics Group Web page at the University of Girona (http://eia.udg.es/_rafa/mosaicviewer.html)

Small scale underwater change detection

In this paper, we present a method to deal with the constraints of the underwater medium for finding changes between sequences of underwater images. One of the main problems of underwater medium for automatically detecting changes is the low altitude of the camera when taking pictures. This emphasise the parallax effect between the images as they are not taken exactly at the same position. In order to solve this problem, we are geometrically registering the images together taking into account the relief of the scene

Creating large and accurate mosaics of the mid-atlantic ridge

We present an approach for creating image mosaics using navigation data consisting on 3D position estimates provided by sensors such as LBL available in deep water surveys. A central issue with acoustic 3D positioning is that the accuracy is far too low compositing the images within reasonable accuracy