Asymmetrical Half-join Method on Dual Vision Face Recognition

This research proposes a model of face recognition using the method of joining two face images from left and right lens from a stereo vision camera namely half-join method. Half-join method is used in face image normalization processing. The proposed half-join method is a face images joining model, which is called asymmetrical half-join. In asymmetrical half-join method, a RoI (region of interest) of face image from left and right lenses are provided based on axis center of each eye in eye detection. The cropping of face image from asymmetrical half-join model has different width depends on eyes coordinate location. The proposed system shows that the asymmetrical half-join method can produce a better of face recognition rate. The experimental results show that the asymmetrical half-join method has a better recognition rate and computation time than single vision method and symmetrical half-join method

Localization of Mobile Device in Space

Tato diplomová práce se zaměřuje na dostupné možnosti lokalizace na současných mobilních telefonech platformy Android. Zkoumá možnosti lokalizace mobilního zařízení nejen s využitím inerciálních senzorů telefonu, ale také možnosti lokalizace s využitím obrazu integrované kamery. V rámci práce jsou popsána provedená měření dostupných inerciálních senzorů, představen algoritmus vizuální lokalizace a navržen systém využívající obou těchto přístupů.This thesis focuses on the current localization options of the Android mobile phone platform. It explores the possibilities of locating mobile devices not only with the use of inertial sensors, but also the possibility of localization using integrated video camera. The work describes the measurements done with available inertial sensors, introduces visual localization algorithm and design a system using these two approaches.

Estimation of Depth Maps from Monocular Images using Deep Neural Networks

Computer vision tasks have seen recent improvements thanks to the development of deep learning and high-end hardware. One of these tasks is depth perception, which involves extracting three-dimensional information from two-dimensional elements like images and constructing a depth map. This kind of information is useful in many domains such as autonomous vehicles or scene reconstruction for augmented and virtual reality. Hu-mans and some other animals achieve this by using binocular vision (vision from two images) and some algorithms have been developed to imitate this process. However, re-cent progress has enabled the advancement of other approaches that allow monocular vision algorithms to accomplish decent depth maps. In this thesis two monocular deep learning methods (Monodepth and DenseDepth) are explored and compared to each other (and with binocular and monocular approaches in general). This experiment is conducted by exposing the two methods to images that have not been seen during training and per-forming a qualitative analysis of their results in two different scenarios: indoors and out-doors. Both Monodepth and DenseDepth are able to produce depth maps, but DenseDepth results are more promising and reliable. Results show the importance of the training do-main, as the accuracy is affected by the choice of pre-trained models, as well as the col-lection and selection of data. It is still an open problem and seems unlikely that monocular depth perception could replace other sensors in critical systems like autonomous driving. However, it could still be a great complement or useful in other products or domains like photography.Doble Grado en Ingeniería Informática y Administración de Empresa

Simulación de un entorno real utilizando holofonías

[EN] The holophony is a technique of spatialization of sound. A holophony is equivalent to a hologram, considering the use of images. Its applications can be diverse and among them can be included to being able to be immersed in a concert in your living room or guiding for blind people. In this Master's Thesis, it is proposed to generate holophonics making use of the capture and processing of real-world scene. As development tools Unity, OpenCV and OpenAL will be used.[ES] La holofonía es una técnica de espacialización sonora. Una holofonía es equivalente a una holografía, si se considera el uso de imágenes. Sus aplicaciones pueden ser diversas y entre ellas cabe destacar el poder estar inmerso en un concierto en el salón de tu casa o el guiado para invidentes. En este Trabajo Fin de Máster se propone generar holofonías utilizando para ello la captura y procesamiento de la escena del mundo real. Como herramientas de desarrollo se utilizará Unity, OpenCV y OpenAL.Prieto López, AE. (2016). Simulación de un entorno real utilizando holofonías. http://hdl.handle.net/10251/77627TFG

Studio ed implementazione di algoritmi di stereo vision in ambito mobile: l'applicazione "SuperStereo"

L'analisi di un'immagine con strumenti automatici si è sviluppata in quella che oggi viene chiamata "computer vision", la materia di studio proveniente dal mondo informatico che si occupa, letteralmente, di "vedere oltre", di estrarre da una figura una serie di aspetti strutturali, sotto forma di dati numerici. Tra le tante aree di ricerca che ne derivano, una in particolare è dedicata alla comprensione di un dettaglio estremamente interessante, che si presta ad applicazioni di molteplici tipologie: la profondità. L'idea di poter recuperare ciò che, apparentemente, si era perso fermando una scena ed imprimendone l'istante in un piano a due dimensioni poteva sembrare, fino a non troppi anni fa, qualcosa di impossibile. Grazie alla cosiddetta "visione stereo", invece, oggi possiamo godere della "terza dimensione" in diversi ambiti, legati ad attività professionali piuttosto che di svago. Inoltre, si presta ad utilizzi ancora più interessanti quando gli strumenti possono vantare caratteristiche tecniche accessibili, come dimensioni ridotte e facilità d'uso. Proprio quest'ultimo aspetto ha catturato l'attenzione di un gruppo di lavoro, dal quale è nata l'idea di sviluppare una soluzione, chiamata "SuperStereo", capace di permettere la stereo vision usando uno strumento estremamente diffuso nel mercato tecnologico globale: uno smartphone e, più in generale, qualsiasi dispositivo mobile appartenente a questa categoria