Frequency decomposition techniques for increased discriminative 3D facial information capture

Eigen-based techniques and other monolithic approaches to face recognition have long been a cornerstone in the face recognition community due to the high dimensionality of face images. Eigen-face techniques provide minimal reconstruction error and limit high-frequency content while linear discriminant-based techniques (fisher-faces) allow the construction of subspaces which preserve discriminatory information. This paper presents a frequency decomposition approach for improved face recognition performance utilising three well-known techniques: Wavelets; Gabor / Log-Gabor; and the Discrete Cosine Transform. Experimentation illustrates that frequency domain partitioning prior to dimensionality reduction increases the information available for classification and greatly increases face recognition performance for both eigen-face and fisher-face approaches.

The patella morphology in trochlear dysplasia : a comparative MRI study

BACKGROUND: Trochlear dysplasia is suspected to have a genetic basis and causes recurrent patellar instability due to insufficient anatomical geometry. Numerous studies about trochlear morphology and the optimal surgical treatment have been carried out, but no attention has been paid to the corresponding patellar morphology.----- ----- PURPOSE: The aim of this study was the evaluation of the patellar morphology in normal and trochlear dysplastic knees. ----- ----- STUDY DESIGN: Biometric analysis. ----- ----- METHODS: Twenty two patellae with underlying trochlear dysplasia (study group--SG) were compared with 22 matched knees with normal trochlear shape (control group--CG) on transverse and sagittal MRI slices. We compared transverse diameter, cartilaginous thickness, Wiberg-index and -angle, length and radius of lateral and medial facet, patellar shape and angle, retropatellar length, and type of trochlear dysplasia. For statistical analysis we used the Wilcoxon signed ranks test. ----- ----- RESULTS: The transverse and sagittal diameter, mean length of medial patellar facet, and mean cartilaginous and subchondral Wiberg-index showed statistical differences between the two groups. ----- ----- CONCLUSIONS: Although the insufficient trochlear depth and decreased lateral trochlear slope are responsible for patellofemoral instability, the patella shows morphological changes in trochlear dysplastic knees. Its overall size and the medial facet are smaller. Although the femoral sulcus angle is larger, the Wiberg-angle and -index are equal to the control group. This may indicate that the patellar morphology may not be a result of missing medial patellofemoral pressure in trochlear dysplastic knees, but a decreased medial patellofemoral traction. This seems to be caused by hypotrophic medial patellofemoral restraints in combination with an increased lateral patellar tilt, both resulting in a decreased tension onto the medial patella facet. Whether there is a genetic component to the patellar morphology remains open.

Plantar fasciitis : are pain and fascial thickness associated with arch shape and loading?

Background and Purpose Although plantar fascial thickening is a sonographic criterion for the diagnosis of plantar fasciitis, the effect of local loading and structural factors on fascial morphology are unknown. The purposes of this study were to compare sonographic measures of fascial thickness and radiographic measures of arch shape and regional loading of the foot during gait in individuals with and without unilateral plantar fasciitis and to investigate potential relationships between these loading and structural factors and the morphology of the plantar fascia in individuals with and without heel pain. Subjects The participants were 10 subjects with unilateral plantar fasciitis and 10 matched asymptomatic controls. Methods Heel pain on weight bearing was measured by a visual analog scale. Fascial thickness and static arch angle were determined from bilateral sagittal sonograms and weight-bearing lateral foot roentgenograms. Regional plantar loading was estimated from a pressure plate. Results On average, the plantar fascia of the symptomatic limb was thicker than the plantar fascia of the asymptomatic limb (6.1±1.4 mm versus 4.2±0.5 mm), which, in turn, was thicker than the fascia of the matched control limbs (3.4±0.5 mm and 3.5±0.6 mm). Pain was correlated with fascial thickness, arch angle, and midfoot loading in the symptomatic foot. Fascial thickness, in turn, was positively correlated with arch angle in symptomatic and asymptomatic feet and with peak regional loading of the midfoot in the symptomatic limb. Discussion and Conclusion The findings indicate that fascial thickness and pain in plantar fasciitis are associated with the regional loading and static shape of the arch.

Facial expression recognition using facial movement features

Facial expression is an important channel for human communication and can be applied in many real applications. One critical step for facial expression recognition (FER) is to accurately extract emotional features. Current approaches on FER in static images have not fully considered and utilized the features of facial element and muscle movements, which represent static and dynamic, as well as geometric and appearance characteristics of facial expressions. This paper proposes an approach to solve this limitation using ‘salient’ distance features, which are obtained by extracting patch-based 3D Gabor features, selecting the ‘salient’ patches, and performing patch matching operations. The experimental results demonstrate high correct recognition rate (CRR), significant performance improvements due to the consideration of facial element and muscle movements, promising results under face registration errors, and fast processing time. The comparison with the state-of-the-art performance confirms that the proposed approach achieves the highest CRR on the JAFFE database and is among the top performers on the Cohn-Kanade (CK) database.

Improving the performance of facial expression recognition using dynamic, subtle and regional features

Human facial expression is a complex process characterized of dynamic, subtle and regional emotional features. State-of-the-art approaches on facial expression recognition (FER) have not fully utilized this kind of features to improve the recognition performance. This paper proposes an approach to overcome this limitation using patch-based ‘salient’ Gabor features. A set of 3D patches are extracted to represent the subtle and regional features, and then inputted into patch matching operations for capturing the dynamic features. Experimental results show a significant performance improvement of the proposed approach due to the use of the dynamic features. Performance comparison with pervious work also confirms that the proposed approach achieves the highest CRR reported to date on the JAFFE database and a top-level performance on the Cohn-Kanade (CK) database.

Urban maze : A typological investigation in porous morphology and dynamic pedestrian networks

Mixed use typologies and pedestrian networks are two strategies commonly applied in design of the contemporary city. These approaches, aimed towards the creation of a more sustainalble urban environment, have their roots in the traditional, pre-industrial towns; they characterize urban form, articulating the tension between privaate and public realms through a series of typological variations as well as stimulating commercial activity in the city centre. Arcades, loggias and verandas are just some of the elements which can mediate this tension. Historically they have defined physical and social spaces with particular character; in the contemporary city these features are applied to deform the urban form and create a porous, dynamic morphology. This paper, comparing case studies from Italy, Japan and Australia, investigates how the design of the transition zone can define hybrid pedestrian networks, where a clear distinction between the public and private realms is no longer applicable. Pedestrians use the city in a dynamic way, combining trajectories on the public street with ones on the fringe or inside of the private built environment. In some cases, cities offer different pedestrian network possibilities at different times, as the commercial precints are subject to variations in accessibility across various timeframes. These walkable systems have an impact on the urban form and identity of places, redefining typologies and requiring an in depth analysis through plan, section and elevation diagrams.

Evaluation of texture and geometry for dimensional facial expression recognition

Facial expression recognition (FER) algorithms mainly focus on classification into a small discrete set of emotions or representation of emotions using facial action units (AUs). Dimensional representation of emotions as continuous values in an arousal-valence space is relatively less investigated. It is not fully known whether fusion of geometric and texture features will result in better dimensional representation of spontaneous emotions. Moreover, the performance of many previously proposed approaches to dimensional representation has not been evaluated thoroughly on publicly available databases. To address these limitations, this paper presents an evaluation framework for dimensional representation of spontaneous facial expressions using texture and geometric features. SIFT, Gabor and LBP features are extracted around facial fiducial points and fused with FAP distance features. The CFS algorithm is adopted for discriminative texture feature selection. Experimental results evaluated on the publicly accessible NVIE database demonstrate that fusion of texture and geometry does not lead to a much better performance than using texture alone, but does result in a significant performance improvement over geometry alone. LBP features perform the best when fused with geometric features. Distributions of arousal and valence for different emotions obtained via the feature extraction process are compared with those obtained from subjective ground truth values assigned by viewers. Predicted valence is found to have a more similar distribution to ground truth than arousal in terms of covariance or Bhattacharya distance, but it shows a greater distance between the means.

Sparse temporal representations for facial expression recognition

In automatic facial expression recognition, an increasing number of techniques had been proposed for in the literature that exploits the temporal nature of facial expressions. As all facial expressions are known to evolve over time, it is crucially important for a classifier to be capable of modelling their dynamics. We establish that the method of sparse representation (SR) classifiers proves to be a suitable candidate for this purpose, and subsequently propose a framework for expression dynamics to be efficiently incorporated into its current formulation. We additionally show that for the SR method to be applied effectively, then a certain threshold on image dimensionality must be enforced (unlike in facial recognition problems). Thirdly, we determined that recognition rates may be significantly influenced by the size of the projection matrix \Phi. To demonstrate these, a battery of experiments had been conducted on the CK+ dataset for the recognition of the seven prototypic expressions - anger, contempt, disgust, fear, happiness, sadness and surprise - and comparisons have been made between the proposed temporal-SR against the static-SR framework and state-of-the-art support vector machine.

The morphology of service bundling settings

The purpose of this paper is to advance our understanding of what contextual factors influence the service bundling process in an organizational setting. Although previous literature contains insights into the mechanisms underlying bundling and the artefacts for performing the bundling task itself, the body of knowledge seems to lack a comprehensive framework for analysing the actual scenario in which the bundling process is performed. This is required as the scenario will influence the bundling method and the IT support. We address this need by designing a morphological box for analysing bundling scenarios in different organizational settings. The factors featured in the box are systematised into a set of four categories of bundling layers which we identify from reviewing literature. The two core layers in the framework are the service bundling on a type level and on an instance level (i.e. configuration). To demonstrate the applicability and utility of the proposed morphological box, we apply it to assess the underlying differences and commonalities of two different bundling scenarios from the B2B and G2C sectors which stress the differences between bundling on a type and instance level. In addition, we identify several prospects for future research that can benefit from the proposed morphological box.

No evidence for subliminal affective priming with emotional facial expression primes

The present study investigated whether facial expressions of emotion presented outside consciousness awareness will elicit evaluative responses as assessed in affective priming. Participants were asked to evaluate pleasant and unpleasant target words that were preceded by masked or unmasked schematic (Experiment 1) or photographic faces (Experiments 1 and 2) with happy or angry expressions. They were either required to perform the target evaluation only or to perform the target evaluation and to name the emotion expressed by the face prime. Prime-target interval was 300 ms in Experiment 1 and 80 ms in Experiment 2. Naming performance confirmed the effectiveness of the masking procedure. Affective priming was evident after unmasked primes in tasks that required naming of the facial expressions for schematic and photographic faces and after unmasked primes in tasks that did not require naming for photographic faces. No affective priming was found after masked primes. The present study failed to provide evidence for affective priming with masked face primes, however, it indicates that voluntary attention to the primes enhances affective priming.

Discovering the best feature extraction and selection algorithms for spontaneous facial expression recognition

Feature extraction and selection are critical processes in developing facial expression recognition (FER) systems. While many algorithms have been proposed for these processes, direct comparison between texture, geometry and their fusion, as well as between multiple selection algorithms has not been found for spontaneous FER. This paper addresses this issue by proposing a unified framework for a comparative study on the widely used texture (LBP, Gabor and SIFT) and geometric (FAP) features, using Adaboost, mRMR and SVM feature selection algorithms. Our experiments on the Feedtum and NVIE databases demonstrate the benefits of fusing geometric and texture features, where SIFT+FAP shows the best performance, while mRMR outperforms Adaboost and SVM. In terms of computational time, LBP and Gabor perform better than SIFT. The optimal combination of SIFT+FAP+mRMR also exhibits a state-of-the-art performance.

Improved facial expression recognition via uni-hyperplane classification

Large margin learning approaches, such as support vector machines (SVM), have been successfully applied to numerous classification tasks, especially for automatic facial expression recognition. The risk of such approaches however, is their sensitivity to large margin losses due to the influence from noisy training examples and outliers which is a common problem in the area of affective computing (i.e., manual coding at the frame level is tedious so coarse labels are normally assigned). In this paper, we leverage the relaxation of the parallel-hyperplanes constraint and propose the use of modified correlation filters (MCF). The MCF is similar in spirit to SVMs and correlation filters, but with the key difference of optimizing only a single hyperplane. We demonstrate the superiority of MCF over current techniques on a battery of experiments.

Molecules, morphology, and ecology indicate a recent, amphibious ancestry for echidnas

The semiaquatic platypus and terrestrial echidnas (spiny anteaters) are the only living egg-laying mammals (monotremes). The fossil record has provided few clues as to their origins and the evolution of their ecological specializations; however, recent reassignment of the Early Cretaceous Teinolophos and Steropodon to the platypus lineage implies that platypuses and echidnas diverged >112.5 million years ago, reinforcing the notion of monotremes as living fossils. This placement is based primarily on characters related to a single feature, the enlarged mandibular canal, which supplies blood vessels and dense electrosensory receptors to the platypus bill. Our reevaluation of the morphological data instead groups platypus and echidnas to the exclusion of Teinolophos and Steropodon and suggests that an enlarged mandibular canal is ancestral for monotremes (partly reversed in echidnas, in association with general mandibular reduction). A multigene evaluation of the echidna–platypus divergence using both a relaxed molecular clock and direct fossil calibrations reveals a recent split of 19–48 million years ago. Platypus-like monotremes (Monotrematum) predate this divergence, indicating that echidnas had aquatically foraging ancestors that reinvaded terrestrial ecosystems. This ecological shift and the associated radiation of echidnas represent a recent expansion of niche space despite potential competition from marsupials. Monotremes might have survived the invasion of marsupials into Australasia by exploiting ecological niches in which marsupials are restricted by their reproductive mode. Morphology, ecology, and molecular biology together indicate that Teinolophos and Steropodon are basal monotremes rather than platypus relatives, and that living monotremes are a relatively recent radiation.