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Predicting facial attributes from faces in the wild is very challenging due to pose and lighting variations in the real world. The key to this problem is to build proper feature representations to cope with these unfavourable conditions. Given the success of Convolutional Neural Network (CNN) in image classification, the high-level CNN feature, as an(More)
This work treats the topic of how to represent eeciently facial textures, for model-based coding of image sequences depicting human faces. The scheme works by geometrically normalizing the image, i.e., compensating for diierent parameters such as head rotation, facial expressions and diierences in facial geometry. The texture is then transformed using the(More)
In this thesis we study algorithms and architectures that can provide a better Quality of Experience (QoE) for streaming video systems and services. With cases and examples taken from the application scenarios of football on mobile phones, we address the fundamental problems behind streaming video services. Thus, our research results can be applied and(More)
Mobile advertisement (ad for short) is a major financial pillar for developers to provide free mobile apps. However, it is frequently thwarted by ad fraud, where rogue code tricks <i>ad providers</i> by forging ad display or user clicks, or both. With the mobile ad market growing drastically (e.g., from $8.76 billion in 2012 to $17.96 billion in 2013), it(More)
In this paper we consider the problem of tracking of moving human face in front of a video camera in real-time for a Model-based coding (MBC) application. The 3D head tracking in a MBC system could be implemented sequentially as 2D location tracking, coarse 3D orientation estimation and accurate 3D motion estimation. This work focuses on the 2D location(More)
This paper addresses an important issue, how to evaluate a vision-based face tracking system? Although nowadays it is getting popular to employ a magnetic sensor to evaluate the performance of such systems. The related issues such as condition and limitation of usage are often omitted. In this paper we studied this accepted evaluation methodology together(More)
Neural networks can easily fall into a local extremum and have slow convergence rate. Quantum Genetic Algorithm (QGA) has features of small population size and fast convergence. Based on the investigation of QGA, we propose a novel neural network model, Radial Basis Function (RBF) networks optimized by Quantum Genetic Algorithm (QGA-RBF model). Then we(More)
In this paper, we introduce the Block Matching (BM) as an alternative patch-based local matching approach for solving the face recognition problem. The Block Matching enables an image patch of the probe face image to search for its best matching from displaced positions in the gallery face image. This matching strategy is very effective for handling spatial(More)