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We present a new Cascaded Shape Regression (CSR) architecture, namely Dynamic Attention-Controlled CSR (DAC-CSR), for robust facial landmark detection on unconstrained faces. Our DAC-CSR divides facial landmark detection into three cascaded sub-tasks: face bounding box refinement, general CSR and attention-controlled CSR. The first two stages refine initial face bounding boxes and output intermediate...
We present a framework for robust face detection and landmark localisation of faces in the wild, which has been evaluated as part of `the 2nd Facial Landmark Localisation Competition'. The framework has four stages: face detection, bounding box aggregation, pose estimation and landmark localisation. To achieve a high detection rate, we use two publicly available CNN-based face detectors and two proprietary...
Metamaterials are the artificial materials composed of multiple individual elements in specially designed periodic subwavelength patterns. The properties of these metamaterials strongly depend on the featured shape or size of the unit of metamaterials rather than the original properties of the composition of materials. Their precise shape, geometry, size, orientation and arrangement can affect the...
In the paper, we consider the probability of applying hyper-spectral image (HSI) processing methods to panchromatic images (PIs), which is a novel yet crucial issue for further analyses. To achieve the purpose, we propose an effective approach for handling PI with HSI unmixing methods. In the approach, HSI simulating process is first implemented to obtain a synthetic HSI from PI. After that, a hyperspectral...
Many real applications, such as network traffic monitoring, intrusion detection, satellite remote sensing, and electronic business, generate data in the form of a stream arriving continuously at high speed. Clustering is an important data analysis tool for knowledge discovery. Compared with traditional clustering algorithms, clustering stream data is an important and challenging problem which has...
It has been shown that multilinear subspace analysis is a powerful tool to overcome difficulties posed by viewpoint, illumination and expression variations in Active Appearance Model(AAM). However, the Higher Order Singular Value Decomposition (HOSVD) in multilinear analysis requires training samples to build the training tensor, which include face images under all different variations. It is hard...
Sensor network is a novel technology about acquiring and processing information. One fundamental issue in sensor network is the sensor placement issue, which affects the performance and lifetime of the network. Aiming at the coverage problem which is mainly considered in sensor node placement, this paper proposes an optimal sensor node placement algorithm which meets different requirements of coverage...
A new video surveillance object recognition algorithm is presented, in which improved invariant moments and length-width ratio of object are extracted as shape feature, while color histograms of object are utilized as color feature. On the combination of shape and color features, object recognition is achieved. Based on the algorithm, an intelligent video surveillance system is implemented. Test results...
A gradient vector flow (GVF) snake based method was proposed for pedicle segmentation in vertebral radiographs. Since pedicles were oval-shaped, the elliptical shape prior was used to constrain the evolution of the GVF snake. From segmented pedicles, some landmarks were automatically identified for 3D stereoradiographic reconstruction of vertebrae to reduce the observer variability. Ten radiographs...
ASM (active shape model) and AAM (active appearance model) model are both parametric model based on statistics. We can locate the key points of a face by AAM model accurately. There is a shape model both in the ASM and AAM. When we build the ASM model and AAM model, we must align the shapes of the training set to a unified framework. In the original alignment process, there are only scale, rotation...
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