Papers by Bernard Tiddeman
A U-Net Architecture for Inpainting Lightstage Normal Maps
Computers, Feb 19, 2024
Construction and visualisation of three-dimensional facial statistics
Computer Methods and Programs in Biomedicine, Sep 1, 2000
This paper presents a new method for the construction of three-dimensional (3D) probabilistic fac... more This paper presents a new method for the construction of three-dimensional (3D) probabilistic facial averages and demonstrates the potential for applications in clinical craniofacial research and patient assessment. Averages are constructed from a database of registered laser-range scans and photographic images using feature based image warping. Facial features are extracted using a template of connected contours, adapted to each subject interactively using snakes. Each subject's images are warped to the average template shape and the mean depth, colour and covariance matrix is found at each point. Statistical comparison of individuals with an average or between two averages is visualised by converting the probabilities to a coloured texture map.
Supplementary material from Colour plasticity in response to social context and parasitic infection in a self-fertilizing fish
Statistical details
Groupwise image alignment automatically provides non-rigid registration across a set of images. I... more Groupwise image alignment automatically provides non-rigid registration across a set of images. It has found applications in facial image analysis and medical image analysis by automatically generating statistical models of shape and appearance. The main approaches used previously include iterative and graph-based approaches. In iterative approaches, the registration of each image is iteratively updated to minimise an error measure across the set. Various metrics and optimisation strategies have been proposed to achieve this. Graph-based methods perform registration of each pair of images in the set, to form a weighted graph of the "distance" between all the images, and then finds the optimal paths between the most central image and every other image. In this paper, we use a graph-based approach to perform initialisation, which is then refined with an iterative approach. Pairwise registration is performed using demons registration, then shortest paths identified in the resulting graph are used to provide an initial warp for each image by concatenating warps along the path. The warps are refined using an iterative Levenberg-Marquardt minimisation to the mean, based on updating the locations of a small number of points and incorporating a stiffness constraint. This optimisation approach is efficient, has very few free parameters to tune and we show how to tune the few remaining parameters. We compare the combined approach to both the iterative and graph-based approaches used independently. Results demonstrate that the combined method improves the alignment of various datasets, including two face datasets and a difficult medical dataset of prostate MRI images. •Computing methodologies → Computer vision; Matching; Image processing;
In this paper we describe a system for facial feature detection and tracking using a 3D extension... more In this paper we describe a system for facial feature detection and tracking using a 3D extension of the Constrained Local Model (CLM) algorithm. The use of a 3D shape model allows improved tracking through large head rotations. CLM uses a shape and texture appearance model to generate a set of region template detectors. A search is then performed in the global pose / shape space using these detectors. The proposed extension uses multiple appearance models from different viewpoints and a single 3D shape model built using Principal Geodesic Analysis (PGA) instead of direct Principal Components Analysis (PCA). During fitting or tracking the current estimate of pose is used to select the appropriate appearance model. We demonstrate our results by fitting the model to image sequences with large head rotations. The results show that the proposed multi-view 3D CLM algorithm using PGA improves the performance of the algorithm using PCA for tracking faces in videos with large out-of-plane head rotations.
International Conference in Central Europe on Computer Graphics and Visualization, 2004
In this paper we describe a new method for improving the representation of textures in blends of ... more In this paper we describe a new method for improving the representation of textures in blends of multiple images based on a Markov Random Field (MRF) algorithm. We show that direct application of an MRF texture synthesis algorithm across a set of images is unable to capture both the "averageness" of the global image appearance as well as specific textural components. To overcome this problem we vary the width of the Parzen window (used to smooth the conditional probability distribution of the pixel's intensity) as a function of scale, thus making lower pyramid resolutions closer to the Gaussian mean, while maintaining the high resolution textures. We also show that approximating the maxima of the conditional probability distributions with a weighted-average produces very similar results with a significant increase in speed.
Facial Feature Detection Under Various Illuminations
Springer eBooks, Nov 21, 2007
ABSTRACT An efficient and robust method to locate eyes and lip corners under various illumination... more ABSTRACT An efficient and robust method to locate eyes and lip corners under various illumination conditions is presented in this paper. First, a global illumination balance method is presented to compensate for variations in illumination and accentuate facial feature details. Next, a human face is distinguished from background based on Haar-like features. After that, eyes are found based on their intensity characteristics and Haar-like features. The lip region is estimated using the positions and sizes of face and eyes. Then, a novel local illumination balance technique, based on an integral projection analysis, is proposed to correct for the non-uniform illumination in the lip region. Finally, lip corners are detected based on their intensity and geometric characteristics. Encouraging results have been obtained using the proposed method.
Royal Society Open Science, Jul 1, 2019
Many animal species rely on changes in body coloration to signal social dominance, mating readine... more Many animal species rely on changes in body coloration to signal social dominance, mating readiness and health status to conspecifics, which can in turn influence reproductive success, social dynamics and pathogen avoidance in natural populations. Such colour changes are thought to be controlled by genetic and environmental conditions, but their relative importance is difficult to measure in natural populations, where individual genetic variability complicates data interpretation. Here, we studied shifts in melanin-related body coloration in response to social context and parasitic infection in two naturally inbred lines of a self-fertilizing fish to disentangle the relative roles of genetic background and individual variation. We found that social context and parasitic infection had a significant effect on body coloration that varied between genetic lines, suggesting the existence of genotype by environment interactions. In addition, individual variation was also important for some of the colour attributes. We suggest that the genetic background drives colour plasticity and that this can maintain phenotypic variation in inbred lines, an adaptive mechanism that may be particularly important when genetic diversity is low.
Lecture Notes in Computer Science, 2008
We present an automatic lip contour extraction and tracking method based on an improved active co... more We present an automatic lip contour extraction and tracking method based on an improved active contour model, which introduces a novel image gradient detection based on the segmented lip, tongue and oral cavity image obtained using a nonlinear transformation of the YCbCr color space and a novel entropy analysis based segmentation. The proposed method provides encouraging results with different mouth shapes (with the appearance of teeth, tongue and oral cavity) under various illuminations.
Robust Facialfeature Tracking Under Variousilluminations
An efficient and robust facial tracking system is presented in this paper. The system is capable ... more An efficient and robust facial tracking system is presented in this paper. The system is capable of distinguishing a human face from a complex background using motion and histogram based methods. We correct for variations in illumination using a mixture of local and global illumination balance techniques. We detect and track six facial feature points i.e. pupils, nostrils and lip
Performance Evaluation of Video Summaries Using Efficient Image Euclidean Distance
Lecture Notes in Computer Science, 2016
Video summarization aims to manage video data by providing succinct representation of videos, how... more Video summarization aims to manage video data by providing succinct representation of videos, however its evaluation is somewhat challenging. IMage Euclidean Distance (IMED) has been proposed for the measurement of the similarity of two images. Though it is effective and can tolerate the distortion and/or small movement of the objects, its computational complexity is high in the order of \(O(n^2)\). This paper proposes an efficient method for evaluating the video summaries. It retrieves a set of matched frames between automatic summary and the ground truth summary through two way search, in which the similarity between two frames are measured using the Efficient IMED (EIMED), which considers neighboring pixels, rather than all the pixels in the frames. Experimental results based on a publicly accessible dataset has shown that the proposed method is effective in finding precise matches and usually discards the false ones, leading to a more objective measurement of the performance for various techniques.
This paper describes an improved system for locating facial features in images using constrained ... more This paper describes an improved system for locating facial features in images using constrained local models (CLM). CLM links a set of local patch classifiers via a PCA shape model for non-rigid alignment and tracking. The convex quadratic fitting (CQF) approach to CLM approximates the patch responses with quadratic functions, allowing the parameter updates to be calculated directly. The Bayesian CLM (BCLM) further extended this approach framing it as a Bayesian inference problem. We further extend the BCLM approach to enable the use of 3D shape models. A 3D shape model is preferred on theoretical grounds and improved performance is confirmed via an empirical evaluation. The extension to 3D is developed by first introducing a full similarity transform to the (linearized) 2D CQF error function. The minimization of this error function gives a set of parameter updates that can be combined with the current estimates via a compositional approach. The adaptation of the algorithm to 3D then follows directly. The resulting algorithm is evaluated on the labeled faces in the wild (LFW) dataset and the results show improved performance over both 2D BCLM and 3D CLM.
A robust facial feature tracking system
ABSTRACT Facial feature tracking is crucial in computer vision applications. In this paper, we pr... more ABSTRACT Facial feature tracking is crucial in computer vision applications. In this paper, we propose a system capable of locating a human face using skin color filtering and then detecting and tracking six facial features, i.e. pupils, nostrils and lip corners, in a real time video. A 3D facial feature model is employed to estimate the 3D pose of a person's head, which improves the robustness of the tracking system. This system has the advantage of automatically detecting the facial features and recovering the features lost during the tracking process. Encouraging results have been obtained using the proposed system.
PLOS ONE, Jan 4, 2016
Adults prefer to interact with others that are similar to themselves. Even slight facial selfrese... more Adults prefer to interact with others that are similar to themselves. Even slight facial selfresemblance can elicit trust towards strangers. Here we investigate if preschoolers at the age of 5 years already use facial self-resemblance when they make social judgments about others. We found that, in the absence of any additional knowledge about prospective peers, children preferred those who look subtly like themselves over complete strangers. Thus, subtle morphological similarities trigger social preferences well before adulthood.
A pertinent evaluation of automatic video summary
Video summarization is useful to find a concise representation of the original video, nevertheles... more Video summarization is useful to find a concise representation of the original video, nevertheless its evaluation is somewhat challenging. This paper proposes a simple and efficient method for precisely evaluating the video summaries produced by the existing techniques. This method includes two steps. The first step is to establish a set of matched frames between automatic summary (AT) and the ground truth summary (GT) through two-way search, in which the similarity between two frames are measured using correlation coefficient. The second step is to estimate the consistency among these established matches, so that the difference among these frames in the AT and GT are preserved respectively. To accomplish this, a compatibility matrix is built based on the features extracted from each of these frames. The consistency values among these matched frames are estimated as the eigenvector of this matrix corresponding to the maximum eigenvalue. Such matched frames with a small enough consistency value will be rejected, leading to more accurate performance estimation of the video summarization techniques. Experimental results based on a publicly accessible dataset shows that the proposed method is effective in finding true matches and provide more realistic measurement of the performance for various techniques.
Groupwise Non-Rigid Image Alignment Using Few Parameters
IGI Global eBooks, Sep 9, 2022
Contact-Free Pulse Signal Extraction from Human Face Videos: A Review and New Optimized Filtering Approach
Advances in Experimental Medicine and Biology, 2021
In this chapter, we review methods for video-based heart monitoring, from classical signal proces... more In this chapter, we review methods for video-based heart monitoring, from classical signal processing approaches to modern deep learning methods. In addition, we propose a new method for learning an optimal filter that can overcome many of the problems that can affect classical approaches, such as light reflection and subject's movements, at a fraction of the training cost of deep learning approaches. Following the usual procedures for region of interest extraction and tracking, robust skin color estimation and signal pre-processing, we introduce a least-squares error optimal filter, learnt using an established training dataset to estimate the photoplethysmographic (PPG) signal more accurately from the measured color changes over time. This method not only improves the accuracy of heart rate measurement but also resulted in the extraction of a cleaner pulse signal, which could be integrated into many other useful applications such as human biometric recognition or recognition of emotional state. The method was tested on the DEAP dataset and showed improved performance over the best previous classical method on that dataset. The results obtained show that our proposed contact-free heart rate measurement method has significantly improved on existing methods.
Robust Facial Feature Tracking Using an Autoregressive Model and Optical Flow
Advanced Science, Engineering and Medicine, Dec 1, 2012
ABSTRACT A robust facial feature tracking system using the Autoregressive model based prediction ... more ABSTRACT A robust facial feature tracking system using the Autoregressive model based prediction and the optical flow based motion detector is proposed in this paper to track six facial features, i.e., two pupils, nostrils and lip corners. In order to improve the robustness of the tracking system, a simple facial feature model was employed to estimate the relative face poses. This system has the advantage of automatically detecting the facial features and recovering the features lost during the tracking process by re-initialization. Encouraging results have been obtained using the proposed system.
Computer-generated face models
Cambridge University Press eBooks, May 3, 2012
Tiddeman, B. (2012). Computer-generated face models. In Wilkinson, C., & Rynn, C. (Eds.), Cra... more Tiddeman, B. (2012). Computer-generated face models. In Wilkinson, C., & Rynn, C. (Eds.), Craniofacial Identification. (pp. 115-124). Cambridge University Press. Chapter 10
A real-time stereo head pose tracking system
ABSTRACT Head pose tracking is very important in many human machine interfaces. In this paper, a ... more ABSTRACT Head pose tracking is very important in many human machine interfaces. In this paper, a stereo head pose tracking system is proposed, which detects and tracks six facial features (pupils, nostrils and lip corners) automatically when a human face appears in front of two low-cost USB cameras. The epipolar constraint and a 3D facial feature model are used to improve the accuracy and robustness of the system. This system has the advantages of automatically detecting the facial features and recovering the features lost during the tracking process. Encouraging results have been obtained using the proposed system