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Presented is an extension of the non-negative matrix factorisation (NMF) by imposing an orthogonality constraint on the basis matrix and controlling the sparseness of the coefficient matrix for robust learning of compact local part-based representation of face images. The extended NMF is solved by a projected gradient algorithm with a data-driven initialisation scheme. In addition, an indicator is...
This study presents a stochastic framework in which incomplete training data are used to boost the accuracy of segmentation and to optimise segmentation when images under consideration are corrupted by inhomogeneities. The authors propose a semi-supervised maximum a posteriori probability (ssMAP) segmentation method that is able to utilise any amount of training data that are usually insufficient...
In this paper we propose a new kernel PCA (KPCA) speed-up algorithm that aims to find a reduced KPCA to approximate the kernel mapping. The algorithm works by greedily choosing a subset of the training samples that minimizes the mean square error of the kernel mapping between the original KPCA and the reduced KPCA. Experimental results have shown that the proposed algorithm is more efficient in computation...
This paper proposes generalised integral image features (GIIFs) for face detection. GIIFs provide a richer and more flexible set of features than Haar-like features. Due to the large set of possible GIIFs, a genetic algorithm is developed to select the feature space for the optimal weak classifiers. Experimental results have shown that this method is able to improve face detection accuracy.
This paper proposes a novel weighted template matching method. It employs a generalized distance transform (GDT) and an orientation map (OM). The GDT allows us to weight the distance transform more on the strong edge points and the OM provides supplementary local orientation information for matching. Based on the matching method, a two-stage human detection method consisting of template matching and...
Although research show that human recognition performance for unfamiliar faces is relatively poor, when the sample is always available for analysis and becomes ??familiar??, people are able to recognize a previous unknown face from single sample. In this paper, a method is proposed to deal with the one sample per person face recognition problem based on the process how unfamiliar faces become familiar...
This paper proposes a part-based template matching method for multi-view human detection. The proposed method includes two stages: matching and verification. In particular, the best individual matching parts given a detection window are determined using an improved template matching algorithm. The hypothesis of the matched parts forming a human is then verified by employing a Bayesian-based model...
Motivated by the non-linear manifold learning ability of the kernel principal component analysis (KPCA), we propose in this paper a method for detecting human postures from single images by employing KPCA to learn the manifold span of a set of HOG features that can effectively represent the postures. The main contribution of this paper is to apply the KPCA as a non-linear learning and open-set classification...
This paper proposes a new two-stage human detection method involving matching and verification. A Bayesian framework is developed to verify the matching score obtained from a weighted distance measure. Performance evaluation indicates that the proposed method is able to utilize the flexible matching scheme and produce superior true positive, true negative and low misclassification rates.
Based on the observation that an attack applied on a watermarked image, from a decoding point of view, modifies the distribution of the detection values away from the ideal distribution (without attack) for corresponding watermarking scheme, we propose a generic maximum likelihood decoding scheme by approximating the distribution with a finite Gaussian mixture model. The parameters of the model are...
Robust image watermarking systems are required to be resistant to geometric attacks in addition to common image processing tasks, such as JPEG compression. However, robustness against geometric attacks, such as rotation, scaling and translation, still remains one of the most challenging research topics in image watermarking. We propose a new pixel-based watermarking system in which a binary logo is...
The concept of the shortest (or minimum) spanning tree (SST)and recursive SST (RSST) of an undirected weighted graph has been successfully applied in image segmentation and edge detection. This paper presents a divide-and-conquer approach for (R)SST based image segmentation in order to overcome the problem of high computational complexity associated with conventional graph algorithms. In the simplest...
Based on K-means and a two-layer pyramid structure, a fast algorithm is proposed for color image segmentation. The algorithm employs two strategies. Firstly, a two-layer structure of a color image is established. Then, an improved K-means with integer based lookup table implementation is applied to each layer. The clustering result on the upper layer (lower resolution) is used to guide the clustering...
We propose a secure video authentication algorithm that is tolerant to visual degradation due to MPEG lossy compression to a designed level. The authentication process generates a tag that is sent with video data and the level of protection can be adjusted so that longer tags are used for higher security, and that the protection is distributed such that higher security is provided for regions of interest...
Despite the increasing interest in multimedia data retrieval audio data has received little attention. This is due, not to a lack of interest but rather to unique difficulties posed by the medium. In particular existing unstructured audio representations do not easily lend themselves to content based retrieval and especially browsing. This paper aims to address this oversight by developing an audio...
This paper describes the application of human visual models in (i) defining a visually uniform colour representation space and (ii) the formulation of visually weighted Kalman filtering for image restoration. The former being useful in colour image quantisation and compression. For (i), the uniformity of chromaticity differences at the output of Frei's (1976) colour vision model is tested and compensated...
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