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.

Mechanical evaluation of a new minimally invasive device for stabilization of proximal humeral fractures in elderly patients : a cadaver study

BACKGROUND: Treatment of proximal humerus fractures in elderly patients is challenging because of reduced bone quality. We determined the in vitro characteristics of a new implant developed to target the remaining bone stock, and compared it with an implant in clinical use. METHODS: Following osteotomy, left and right humeral pairs from cadavers were treated with either the Button-Fix or the Humerusblock fixation system. Implant stiffness was determined for three clinically relevant cases of load: axial compression, torsion, and varus bending. In addition, a cyclic varus-bending test was performed. RESULTS: We found higher stiffness values for the humeri treated with the ButtonFix system--with almost a doubling of the compression, torsion, and bending stiffness values. Under dynamic loading, the ButtonFix system had superior stiffness and less K-wire migration compared to the Humerusblock system. INTERPRETATION: When compared to the Humerusblock design, the ButtonFix system showed superior biomechanical properties, both static and dynamic. It offers a minimally invasive alternative for the treatment of proximal humerus fractures.

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.

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.

Cerclage, evolution and potential of a Cinderella Technology : an overview with reference to periprosthetic fractures

Periprosthetic fractures are increasingly frequent. The fracture may be located over the shaft of the prosthesis, at its tip or below (21). The treatment of explosion fractures is difficult because the shaft blocks the application of implants, like screws, which need to penetrate the medullary cavity. The cerclage, as a simple periosteal loop, made of wire or more recently cable, does not only avoid the medullary cavity. Its centripetal mode of action is well suited for reducing and maintaining radially displaced fractures. Furthermore, the cerclage lends itself well for minimally invasive internal fixation. New insight challenges the disrepute of which the cerclage technology suffered for decades. The outcome of cerclage fixation benefits from an improved understanding of its technology, mechano-biology and periosteal blood supply. Preconceived and generally accepted opinions like "strangulation of blood supply" need to be re-examined. Recent mechanical evaluations (22) demonstrate that the wire application may be improved but cable is superior in hand- ling, maintenance of tension and strength. Beside the classical concepts of absolute and relative stability a defined stability condition needs consideration. It is typical for cerclage. Called "loose-lock stability" it specifies the situation where a loosened implant allows first unimpeded displacement changing abruptly into a locked fixation preventing further dislocation.

Technical note : a technique for measuring the surface area of articular cartilage in acetabular fractures

The aim of this study was to develop a reliable technique for measuring the area of a curved surface from an axial computed tomography (CT) scan and to apply this clinically in the measurement of articular cartilage surface area in acetabular fractures. The method used was a triangulation algorithm. In order to determine the accuracy of the technique, areas of hemispheres of known size were measured to give the percentage error in area measurement. Seven such hemispheres were machined into a Perspex block and their area measured geometrically, and also from CT scans by means of the triangulation algorithm. Scans of 1, 2 and 4 mm slice thickness and separation were used. The error varied with slice thickness and hemisphere diameter. It was shown that the 2 mm slice thickness provides the most accurate area measurement, while 1 mm cuts overestimate and 4 mm cuts underestimate the area. For a hemisphere diameter of 5 cm, which is of similar size to the acetabulum, the error was -11.2% for 4 mm cuts, +4.2% for 2 mm cuts and + 5.1% for 1 mm cuts. As expected, area measurement was more accurate for larger hemispheres. This method can be applied clinically to quantify acetabular fractures by measuring the percentage area of intact articular cartilage. In the case of both column fractures, the percentage area of secondary congruence can be determined. This technique of quantifying acetabular fractures has a potential clinical application as a prognostic factor and an indication for surgery in the long term.