3D Reconstruction using Active Illumination

In this thesis we present a pipeline for 3D model acquisition. Generating 3D models of real-world objects is an important task in computer vision with many applications, such as in 3D design, archaeology, entertainment, and virtual or augmented reality. The contribution of this thesis is threefold: we propose a calibration procedure for the cameras, we describe an approach for capturing and processing photometric normals using gradient illuminations in the hardware set-up, and finally we present a multi-view photometric stereo 3D reconstruction method. In order to obtain accurate results using multi-view and photometric stereo reconstruction, the cameras are calibrated geometrically and photometrically. For acquiring data, a light stage is used. This is a hardware set-up that allows to control the illumination during acquisition. The procedure used to generate appropriate illuminations and to process the acquired data to obtain accurate photometric normals is described. The core of the pipeline is a multi-view photometric stereo reconstruction method. In this method, we first generate a sparse reconstruction using the acquired images and computed normals. In the second step, the information from the normal maps is used to obtain a dense reconstruction of an object’s surface. Finally, the reconstructed surface is filtered to remove artifacts introduced by the dense reconstruction step

Achieving security despite compromise using zero-knowledge

One of the important challenges when designing and analyzing cryptographic protocols is the enforcement of security properties in the presence of compromised participants. This paper presents a general technique for strengthening cryptographic protocols in order to satisfy authorization policies despite participant compromise. The central idea is to automatically transform the original cryptographic protocols by adding non-interactive zero-knowledge proofs. Each participant proves that the messages sent to the other participants are generated in accordance to the protocol. The zero-knowledge proofs are forwarded to ensure the correct behaviour of all participants involved in the protocol, without revealing any secret data. We use an enhanced type system for zero-knowledge to verify that the transformed protocols conform to their authorization policy even if some participants are compromised. Both the protocol transformation and the verification are fully automated.

3D Reconstruction using Active Illumination

In this thesis we present a pipeline for 3D model acquisition. Generating 3D models of real-world objects is an important task in computer vision with many applications, such as in 3D design, archaeology, entertainment, and virtual or augmented reality. The contribution of this thesis is threefold: we propose a calibration procedure for the cameras, we describe an approach for capturing and processing photometric normals using gradient illuminations in the hardware set-up, and finally we present a multi-view photometric stereo 3D reconstruction method. In order to obtain accurate results using multi-view and photometric stereo reconstruction, the cameras are calibrated geometrically and photometrically. For acquiring data, a light stage is used. This is a hardware set-up that allows to control the illumination during acquisition. The procedure used to generate appropriate illuminations and to process the acquired data to obtain accurate photometric normals is described. The core of the pipeline is a multi-view photometric stereo reconstruction method. In this method, we first generate a sparse reconstruction using the acquired images and computed normals. In the second step, the information from the normal maps is used to obtain a dense reconstruction of an object’s surface. Finally, the reconstructed surface is filtered to remove artifacts introduced by the dense reconstruction step

AUDIO-VISUAL MULTIPLE ACTIVE SPEAKER LOCALISATION IN REVERBERANT ENVIRONMENTS

Localisation of multiple active speakers in natural environments with only two microphones is a challenging problem. Reverberation degrades the performance of speaker localisation based exclusively on directional cues. This paper presents an approach based on audio-visual fusion. The audio modality performs the multiple speaker localisation using the Skeleton method, energy weighting, and precedence effect filtering and weighting. The video modality performs the active speaker detection based on the analysis of the lip region of the detected speakers. The audio modality alone has problems with localisation accuracy, while the video modality alone has problems with false detections. The estimation results of both modalities are represented as probabilities in the azimuth domain. A Gaussian fusion method is proposed to combine the estimates in a late stage. As a consequence, the localisation accuracy and robustness compared to the audio/video modality alone is significantly increased. Experimental results in different scenarios confirmed the improved performance of the proposed method. 1