Automatic Recognition of Leaves by Shape Detection Pre-Processing with Ica

In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.

Statistical model based 3D shape prediction of postoperative trunks for non-invasive scoliosis surgery planning

One of the major concerns of scoliosis patients undergoing surgical treatment is the aesthetic aspect of the surgery outcome. It would be useful to predict the postoperative appearance of the patient trunk in the course of a surgery planning process in order to take into account the expectations of the patient. In this paper, we propose to use least squares support vector regression for the prediction of the postoperative trunk 3D shape after spine surgery for adolescent idiopathic scoliosis. Five dimensionality reduction techniques used in conjunction with the support vector machine are compared. The methods are evaluated in terms of their accuracy, based on the leave-one-out cross-validation performed on a database of 141 cases. The results indicate that the 3D shape predictions using a dimensionality reduction obtained by simultaneous decomposition of the predictors and response variables have the best accuracy.

Representing 3D shape and location

The 3D shape of an object and its 3D location have traditionally thought of as very separate entities, although both can be described within a single 3D coordinate frame. Here, 3D shape and location are considered as two aspects of a view-based approach to representing depth, avoiding the use of 3D coordinate frames.

Improving 3D Keypoint Detection from Noisy Data Using Growing Neural Gas

3D sensors provides valuable information for mobile robotic tasks like scene classification or object recognition, but these sensors often produce noisy data that makes impossible applying classical keypoint detection and feature extraction techniques. Therefore, noise removal and downsampling have become essential steps in 3D data processing. In this work, we propose the use of a 3D filtering and down-sampling technique based on a Growing Neural Gas (GNG) network. GNG method is able to deal with outliers presents in the input data. These features allows to represent 3D spaces, obtaining an induced Delaunay Triangulation of the input space. Experiments show how the state-of-the-art keypoint detectors improve their performance using GNG output representation as input data. Descriptors extracted on improved keypoints perform better matching in robotics applications as 3D scene registration.

Visual perception for the 3D recognition of geometric pieces in robotic manipulation

During grasping and intelligent robotic manipulation tasks, the camera position relative to the scene changes dramatically because the robot is moving to adapt its path and correctly grasp objects. This is because the camera is mounted at the robot effector. For this reason, in this type of environment, a visual recognition system must be implemented to recognize and “automatically and autonomously” obtain the positions of objects in the scene. Furthermore, in industrial environments, all objects that are manipulated by robots are made of the same material and cannot be differentiated by features such as texture or color. In this work, first, a study and analysis of 3D recognition descriptors has been completed for application in these environments. Second, a visual recognition system designed from specific distributed client-server architecture has been proposed to be applied in the recognition process of industrial objects without these appearance features. Our system has been implemented to overcome problems of recognition when the objects can only be recognized by geometric shape and the simplicity of shapes could create ambiguity. Finally, some real tests are performed and illustrated to verify the satisfactory performance of the proposed system.

A problem in form perception: odd shape detection.

"C00-2118-0027."

Live 3D shape reconstruction, recognition and registration

We present a video-based system which interactively captures the geometry of a 3D object in the form of a point cloud, then recognizes and registers known objects in this point cloud in a matter of seconds (fig. 1). In order to achieve interactive speed, we exploit both efficient inference algorithms and parallel computation, often on a GPU. The system can be broken down into two distinct phases: geometry capture, and object inference. We now discuss these in further detail. © 2011 IEEE.

Real-time 3D shape sensing and reconstruction scheme based upon fibre optic bragg gratings

An array of FBG curvature sensors are wavelength-interrogated and the recovered data combined with a three-dimensional algorithm to reconstruct in real time the enveloped object with a 1% to 9% volumetric error. © 2012 OSA.

Does countershading contribute to visual camouflage by concealing 3D shape?

This is an abstract of an invited talk presented at AVA Animal Vision Meeting / Camocon 2015, which took place in Liverpool, 23 August 2015.

Amorphous silicon e 3D sensors applied to object detection

Nowadays, existing 3D scanning cameras and microscopes in the market use digital or discrete sensors, such as CCDs or CMOS for object detection applications. However, these combined systems are not fast enough for some application scenarios since they require large data processing resources and can be cumbersome. Thereby, there is a clear interest in exploring the possibilities and performances of analogue sensors such as arrays of position sensitive detectors with the final goal of integrating them in 3D scanning cameras or microscopes for object detection purposes. The work performed in this thesis deals with the implementation of prototype systems in order to explore the application of object detection using amorphous silicon position sensors of 32 and 128 lines which were produced in the clean room at CENIMAT-CEMOP. During the first phase of this work, the fabrication and the study of the static and dynamic specifications of the sensors as well as their conditioning in relation to the existing scientific and technological knowledge became a starting point. Subsequently, relevant data acquisition and suitable signal processing electronics were assembled. Various prototypes were developed for the 32 and 128 array PSD sensors. Appropriate optical solutions were integrated to work together with the constructed prototypes, allowing the required experiments to be carried out and allowing the achievement of the results presented in this thesis. All control, data acquisition and 3D rendering platform software was implemented for the existing systems. All these components were combined together to form several integrated systems for the 32 and 128 line PSD 3D sensors. The performance of the 32 PSD array sensor and system was evaluated for machine vision applications such as for example 3D object rendering as well as for microscopy applications such as for example micro object movement detection. Trials were also performed involving the 128 array PSD sensor systems. Sensor channel non-linearities of approximately 4 to 7% were obtained. Overall results obtained show the possibility of using a linear array of 32/128 1D line sensors based on the amorphous silicon technology to render 3D profiles of objects. The system and setup presented allows 3D rendering at high speeds and at high frame rates. The minimum detail or gap that can be detected by the sensor system is approximately 350 μm when using this current setup. It is also possible to render an object in 3D within a scanning angle range of 15º to 85º and identify its real height as a function of the scanning angle and the image displacement distance on the sensor. Simple and not so simple objects, such as a rubber and a plastic fork, can be rendered in 3D properly and accurately also at high resolution, using this sensor and system platform. The nip structure sensor system can detect primary and even derived colors of objects by a proper adjustment of the integration time of the system and by combining white, red, green and blue (RGB) light sources. A mean colorimetric error of 25.7 was obtained. It is also possible to detect the movement of micrometer objects using the 32 PSD sensor system. This kind of setup offers the possibility to detect if a micro object is moving, what are its dimensions and what is its position in two dimensions, even at high speeds. Results show a non-linearity of about 3% and a spatial resolution of < 2µm.

A Statistical Image-Based Shape Model for Visual Hull Reconstruction and 3D Structure Inference

We present a statistical image-based shape + structure model for Bayesian visual hull reconstruction and 3D structure inference. The 3D shape of a class of objects is represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes are then estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We show how the use of a class-specific prior in a visual hull reconstruction can reduce the effect of segmentation errors from the silhouette extraction process. The proposed method is applied to a data set of pedestrian images, and improvements in the approximate 3D models under various noise conditions are shown. We further augment the shape model to incorporate structural features of interest; unknown structural parameters for a novel set of contours are then inferred via the Bayesian reconstruction process. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a data set of thousands of pedestrian images generated from a synthetic model, we can accurately infer the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

New Methods for Triangulation-based Shape Acquisition using Laser Scanners

Tradicionalment, la reproducció del mon real se'ns ha mostrat a traves d'imatges planes. Aquestes imatges se solien materialitzar mitjançant pintures sobre tela o be amb dibuixos. Avui, per sort, encara podem veure pintures fetes a ma, tot i que la majoria d'imatges s'adquireixen mitjançant càmeres, i es mostren directament a una audiència, com en el cinema, la televisió o exposicions de fotografies, o be son processades per un sistema computeritzat per tal d'obtenir un resultat en particular. Aquests processaments s'apliquen en camps com en el control de qualitat industrial o be en la recerca mes puntera en intel·ligència artificial. Aplicant algorismes de processament de nivell mitja es poden obtenir imatges 3D a partir d'imatges 2D, utilitzant tècniques ben conegudes anomenades Shape From X, on X es el mètode per obtenir la tercera dimensió, i varia en funció de la tècnica que s'utilitza a tal nalitat. Tot i que l'evolució cap a la càmera 3D va començar en els 90, cal que les tècniques per obtenir les formes tridimensionals siguin mes i mes acurades. Les aplicacions dels escàners 3D han augmentat considerablement en els darrers anys, especialment en camps com el lleure, diagnosi/cirurgia assistida, robòtica, etc. Una de les tècniques mes utilitzades per obtenir informació 3D d'una escena, es la triangulació, i mes concretament, la utilització d'escàners laser tridimensionals. Des de la seva aparició formal en publicacions científiques al 1971 [SS71], hi ha hagut contribucions per solucionar problemes inherents com ara la disminució d'oclusions, millora de la precisió, velocitat d'adquisició, descripció de la forma, etc. Tots i cadascun dels mètodes per obtenir punts 3D d'una escena te associat un procés de calibració, i aquest procés juga un paper decisiu en el rendiment d'un dispositiu d'adquisició tridimensional. La nalitat d'aquesta tesi es la d'abordar el problema de l'adquisició de forma 3D, des d'un punt de vista total, reportant un estat de l'art sobre escàners laser basats en triangulació, provant el funcionament i rendiment de diferents sistemes, i fent aportacions per millorar la precisió en la detecció del feix laser, especialment en condicions adverses, i solucionant el problema de la calibració a partir de mètodes geomètrics projectius.

Détection, reconstruction 3D et identification des êtres vivants du règne animal

L’automatisation de la détection et de l’identification des animaux est une tâche qui a de l’intérêt dans plusieurs domaines de recherche en biologie ainsi que dans le développement de systèmes de surveillance électronique. L’auteur présente un système de détection et d’identification basé sur la vision stéréo par ordinateur. Plusieurs critères sont utilisés pour identifier les animaux, mais l’accent a été mis sur l’analyse harmonique de la reconstruction en temps réel de la forme en 3D des animaux. Le résultat de l’analyse est comparé avec d’autres qui sont contenus dans une base évolutive de connaissances.

3D-muodot tuoliaihion muotopuristuksessa

Diplomityössä tutkittiin muotopuristeissa käytettävien viilujen soveltuvuutta yhteistyöyrityksen, VK Valmiskaluste Oy:n, valmistaman lepotuolin materiaaliksi. Tuoliaihion muoto edellytti viilun taivuttamista kahteen suuntaan, eli kyseessä oli ns. 3D-muoto. Muotopuristeita valmistavissa yrityksissä tehtyjen haastattelujen perusteella valittiin viilumateriaalit ja mitattiin niiden murtovenymä. Materiaaleja testattiin puristamalla tuoliaihioita. Aihionmuoto edellytti viilulta vähintään 3,3 %:n venyvyyttä. Koepuristuksetvahvistivat murtovenymätestauksen tulokset, eli tutkitun aihion pintarakenne säilyi ehjänä käyttämällä paperitaustaista viilua tai 3D-muotoihin tarkoitettua 3D-viilua. Kirjallisuusosiossa on selvitetty taivutettavuuteen vaikuttavia tekijöitä ja viilun rakenteen muokkausta taivutettavuuden parantamiseksi .

L’impact de la stéréoscopie dans la reconnaissance, la perception et la constance de forme 3D

Les buts des recherches présentées dans cette thèse étaient d’évaluer le rôle de la stéréoscopie dans la reconnaissance de forme, dans la perception du relief et dans la constance de forme. La première étude a examiné le rôle de la stéréoscopie dans la perception des formes visuelles en utilisant une tâche de reconnaissance de formes. Les stimuli pouvaient être présentés en 2D, avec disparité normale (3D) ou avec disparité inversée. La performance de reconnaissance était meilleure avec les modes de présentation 2D et 3D qu’avec la 3D inversée. Cela indique que la stéréoscopie contribue à la reconnaissance de forme. La deuxième étude s’est intéressée à la contribution conjointe de l’ombrage et de la stéréoscopie dans la perception du relief des formes. Les stimuli étaient des images d’une forme 3D convexe synthétique présentée sous un point de vue menant à une ambigüité quant à sa convexité. L’illumination pouvait provenir du haut ou du bas et de la gauche ou de la droite, et les stimuli étaient présentés dichoptiquement avec soit de la disparité binoculaire normale, de la disparité inversée ou sans disparité entre les vues. Les participants ont répondu que les formes étaient convexes plus souvent lorsque la lumière provenait du haut que du bas, plus souvent avec la disparité normale qu’en 2D, et plus souvent avec absence de disparité qu’avec disparité inversée. Les effets de direction d’illumination et du mode de présentation étaient additifs, c’est-à-dire qu’ils n’interagissaient pas. Cela indique que l’ombrage et la stéréoscopie contribuent indépendamment à la perception du relief des formes. La troisième étude a évalué la contribution de la stéréoscopie à la constance de forme, et son interaction avec l’expertise perceptuelle. Elle a utilisé trois tâches de discrimination séquentielle de trombones tordus ayant subi des rotations en profondeur. Les stimuli pouvaient être présentés sans stéréoscopie, avec stéréoscopie normale ou avec stéréoscopie inversée. Dans la première moitié de l’Exp. 1, dans laquelle les variations du mode de présentation étaient intra-sujets, les performances étaient meilleures en 3D qu’en 2D et qu’en 3D inversée. Ces effets ont été renversés dans la seconde moitié de l’expérience, et les coûts de rotation sont devenus plus faibles pour la 2D et la 3D inversée que pour la 3D. Dans les Exps. 2 (variations intra-sujets du mode de présentation, avec un changement de stimuli au milieu de l’expérience) et 3 (variations inter-sujets du mode de présentation), les effets de rotation étaient en tout temps plus faibles avec stéréoscopie qu’avec stéréoscopie inversée et qu’en 2D, et plus faibles avec stéréoscopie inversée que sans stéréoscopie. Ces résultats indiquent que la stéréoscopie contribue à la constance de forme. Toutefois, cela demande qu’elle soit valide avec un niveau minimal de consistance, sinon elle devient stratégiquement ignorée. En bref, les trois études présentées dans cette thèse ont permis de montrer que la stéréoscopie contribue à la reconnaissance de forme, à la perception du relief et à la constance de forme. De plus, l’ombrage et la stéréoscopie sont intégrés linéairement.