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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...
We present a region matching algorithm which establishes correspondences between regions from two segmented images. An abstract graph-based representation conceals the image in a hierarchical graph, exploiting the scene properties at two levels. First, the similarity and spatial consistency of the image semantic objects is encoded in a graph of commute times. Second, the cluttered regions of the semantic...
Imaging neural stem cells/ neurospheres using low magnification brightfield modality results in uneven illumination effects across the field of view. Globally, the centre appears bright while the edges appear dark; locally, illumination varies across individual adjacent site images. Furthermore, neurospheres residing in the dark background regions have low signal:noise ratio. Altogether, they impose...
Edges are caused by several imaging cues such as shadow, material and illumination transitions. Classification methods have been proposed which are solely based on photometric information, ignoring geometry to classify the physical nature of edges in images. In this paper, the aim is to present a novel strategy to handle both photometric and geometric information for edge classification. Photometric...
This paper presents a novel algorithm for estimating stereo disparity which exploits the benefit of learning to the fullest. Given a cost volume of stereo matching, we solve the cost aggregation and disparity computation in one shot by using a classifier; we design a feature called matching cost pattern for the input which we extract from the cost volume while we use simulated stereo patterns for...
In this paper, we propose a novel binary-based cost computation and aggregation approach for stereo matching problem. The cost volume is constructed through bitwise operations on a series of binary strings. Then this approach is combined with traditional winner-take-all strategy, resulting in a new local stereo matching algorithm called binary stereo matching (BSM). Since core algorithm of BSM is...
Shape context has been proven to be an effective method for both local feature matching and global context description. In this paper, we propose a method to build a glocal shape context descriptor in cluttered images. By using the proposed keypoint centered multiple scale edge detection (KMSED) method, glocal shape context encodes fine-scale edges in the keypoint center region while coarse-scale...
In biometric studies, quality evaluation of input data is very important, and has proven to have a direct relation with system performance. Quality measures can provide real-time feedback to reduce the number of poor quality submissions to the system. Another benefit is that they can predict and improve the authentication performance (e.g., by using quality-dependent thresholds). This paper main focus...
A new descriptor called Multi-modal Binary Patterns (MMBP) is proposed for face recognition. It balances well important requirements for real-world applications, including the robustness, discriminative power, and the low computational cost. The proposed algorithm has several desirable properties: 1) it captures information from face image in any direction as it is oriented feature, 2) being a spatial...
Some computational photography techniques have been proposed to control the focus and illumination of captured images. However, the relationship between the techniques have been unclear because they were developed independently for different purposes. In this research we propose a unified framework to explain the computational photography techniques in the computation of an 8-D reflectance field....
Environment illumination is a key to achieving a realistic visualization of material appearance. One way to achieve such an illumination is an approximation by rendering of the material surface lit by a finite set of point light sources. In this paper we employed visual psychophysics to identify a minimal number of point light sources approximating realistic illumination. Furthermore, we analyzed...
A general method for image contrast enhancement and noise reduction is proposed in this paper. The method is developed especially for enhancing images acquired under very low light conditions where the features of images are nearly invisible and the noise is serious. By applying an improved and effective image de-haze algorithm to the inverted input image, the intensity can be amplified so that the...
We propose a method for extracting and combining small-scale and large-scale illumination insensitive features for face recognition that can work even in the presence of cast shadows. Although several methods have been proposed to extract such features, they are not designed to handle severe lighting variation on a face and thus fail to work if cast shadows are present. In this paper, we extend quotient...
We developed a motion blur restoration technique for surface orientation images using a correlation image sensor. This system consists of two components; one is ring-shaped modulation illumination for encoding surface orientation into the amplitude and phase of the reflected light intensity, and the other is the three-phase correlation image sensor (3PCIS) for demodulating the amplitude and phase...
In this paper a new block-based algorithm has been proposed to deal with facial occlusion when only one sample per person is available. A Local Binary Pattern (LBP) descriptor is applied on the image subblocks to extract distinctive texture features from those areas separately. Chi-Square is employed as histogram similarity metric in local classifiers corresponding to different image blocks. Finally,...
Capturing appearance of material with respect to illumination and viewing directions is crucial to achieve realistic visual experience in virtual environments. The capturing process is time demanding or requires a specific shape of the captured material. Therefore, we propose a method of such a data reconstruction from very sparse measurements, whose placement allows for continuous and fast acquisition,...
In this paper we propose a new 3D descriptor for people re-identification using depth cameras. The descriptor is based on a 3D cylindrical grid that stores color variations with angle and height. A robust comparison method is also presented. This method ignores variations in brightness and contrast of descriptors obtained at possibly different locations. However it retains the ability to distinguish...
To deal with the drifting issue in visual tracking, we propose an Online Transfer Boosting (OTB) algorithm that transfers knowledge from three different source domains to the target domain to improve the performance of the online classifier used in tracking-by-detection. In particular, the OTB algorithm integrates three types of knowledge by: (1) transferring prior knowledge from the first frame using...
We propose a new component-tree based method with efficient and effective pruning strategies for userintention guided text extraction from scene images. A grayscale image is represented first as two component-trees, whose nodes represent possible candidates of character components. The non-text candidates are then pruned by using contrast, geometric and text line information as well as the constraint...
Optical consistency between the real world and the virtual objects is one of the important issues in Augmented Reality (AR). This paper proposes a method to estimate illuminations from an object shadow and incomplete object shape information captured by an RGB-D camera. The environmental illumination can be estimated without any prior knowledge of the object shape. The radiance of each light source...
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