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2 results on '"3D generic face model"'

1. 3D veido atkūrimas iš nuotraukos

Author

Kačanauskas, Mindaugas, Žiūrienė, Rytė, Filatovas, Ernestas, Baušys, Romualdas, Barauskas, Arūnas, Devenson, Jelena, Mažonavičiūtė, Ingrida, and Vilnius Gediminas Technical University

Subjects
Informatics Engineering, Geometry reconstruction, Veido nuotraukos, 3d face, 3D generic face model, Bendrinis veido modelis, Face pictures, Geometrijos atstatymas, 3d veidas
Abstract

Baigiamajame magistro darbe nagrinėjamos technologijos naudojamos 3D veido atkūrime. Pasirinkus 3D veido atkūrimą iš nuotraukos yra nagrinėjami šio proceso metu naudojami 3D bendriniai modeliai, jų sandara, bei juos naudojantys metodai. Taip pat nagrinėjamas veido savybių taškų aptikimas naudojant aktyvios formos modelius, bendrinio modelio interpoliavimas naudojant plonųjų plokštumų splainų metodą, bei ortogonalus tekstūros projektavimas modeliui. Taip pat pateikiamas naujas siūlomas veido formos modelis aprašantis papildomas savybes. Praktinėje dalyje yra pateikiama sukurta programa, kuri pateikus vieną veido nuotrauką automatiškai atkuria 3D veidą su tekstūra. Gautas 3D veidas gali būti eksportuotas į OBJ formato bylą. Gauti rezultatai yra įvertinami apskaičiuojant paklaidą tarp realių ir atkurtų veidų, naudojant lazeriu nuskaitytų 3D veidų duomenų bazę. The aim of this master thesis is to examine the technologies that are being used for 3D face reconstruction. 3D generic face models, their structure, and methods they are being used with, are being analyzed after selecting reconstruction from single photo technology. Also facial feature points detection while using active shape models, 3D generic face interpolation, and orthogonal texture mapping for model are being analyzed. Also a new facial shape model is defined. Automated 3D face reconstruction application was developed based on previous analysis. Application is capable of automatically reconstructing full 3D face model with texture from single frontal face picture. Resulting face model can be exported to another software by using OBJ file format. The results of application are being evaluated while calculating error between real and reconstructed faces, while using laser scanned 3D face database.

Published
2014

2. Model based methods for locating, enhancing and recognising low resolution objects in video

Abstract

Visual perception is our most important sense which enables us to detect and recognise objects even in low detail video scenes. While humans are able to perform such object detection and recognition tasks reliably, most computer vision algorithms struggle with wide angle surveillance videos that make automatic processing difficult due to low resolution and poor detail objects. Additional problems arise from varying pose and lighting conditions as well as non-cooperative subjects. All these constraints pose problems for automatic scene interpretation of surveillance video, including object detection, tracking and object recognition.Therefore, the aim of this thesis is to detect, enhance and recognise objects by incorporating a priori information and by using model based approaches. Motivated by the increasing demand for automatic methods for object detection, enhancement and recognition in video surveillance, different aspects of the video processing task are investigated with a focus on human faces. In particular, the challenge of fully automatic face pose and shape estimation by fitting a deformable 3D generic face model under varying pose and lighting conditions is tackled. Principal Component Analysis (PCA) is utilised to build an appearance model that is then used within a particle filter based approach to fit the 3D face mask to the image. This recovers face pose and person-specific shape information simultaneously. Experiments demonstrate the use in different resolution and under varying pose and lighting conditions. Following that, a combined tracking and super resolution approach enhances the quality of poor detail video objects. A 3D object mask is subdivided such that every mask triangle is smaller than a pixel when projected into the image and then used for model based tracking. The mask subdivision then allows for super resolution of the object by combining several video frames. This approach achieves better results than traditional super resolution meth

Published
2009

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