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Provides an abstract for each of the keynote presentations and may include a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings.
The process of spatially aligning two or more images acquired from different devices or imaging protocols is known as multi-modal image registration. As the similarity measure used is one of the most significant aspects of this process, certain measures have been proposed to enhance multi-modal image registration. However, the currently available measures are either not sufficiently accurate or are...
Recently, a lot of works have shown the advantages of utilizing the deep descriptors, obtained from the features of the last convolution layer in CNNs, on image retrieval. In this paper, we focus on augmenting and fusing CNN features for the image retrieval task. We first investigate the effects of network rotation, and then propose two models for deep feature augmenting: single model augmenting and...
The measurement of residual thyroid tissue after thyroidectomy is crucial for the precise quantification of thyroid cancer treatment. Accurate residual thyroid tissue segmentation from CT images is challenging due to the indistinct tissue boundary. We propose a vote-in & vote-out region propagation model for residual thyroid tissue segmentation which incorporates global and local constraints and...
This paper describes an objective and subjective evaluation models of pencil still drawings for art education. In the subjective evaluation, the evaluation word is summarized. This is a point of view when an art educator evaluates a pencil still drawing. The objective evaluation model consists of factor Fi, which comprises the features value of a basic pencil still drawing. Fi is also defined by considering...
Motion vectors extracted from a compressed video file can be used to track objects in the video and it could be efficient as motion vectors provide trajectory information of the objects. However, tracking objects represented by the motion vectors can be inaccuracy because of camera movement, small size sets of motion vectors acting as noise, unmoving of the object and occlusion. These are conditions...
Dictionary learning algorithms have received widespread acceptance when it comes to data analysis and signal representation problems. However, most existing algorithms assume isotropic noise. This is a restrictive assumption as the noise across samples may be nonuniform in a number of real world application. The aim of this article is to propose a sequential dictionary learning algorithm for measurement...
With the development of displaying techniques, free viewpoint video (FVV) system shows its potential to provide immersive perceptual feeling by changing viewpoints. To provide this luxury, a large number of high quality views have to be synthesised from limited number of viewpoints. However, in this process, a portion of the background is occluded by the foreground object in the generated synthesised...
This paper develops a general framework of image retrieval, named A3, by introducing an auxiliary set of samples (object references), each of which is annotated with semantic attributes (tags). Given a query image (without tags), we first map it into the references by a non-convex sparse coding formulation, which jointly optimizes appearance reconstruction of the query and semantics consistency among...
Automatic face retrieval or verification is a matter to identify whether the target person is the same person, which has been received considerable attention by researchers in computer vision. This paper proposes a method to localize a face from video sequences by considering only one shot. First, Cascade AdaBoost is applied to identify region of a face from the video sequence. The image enhancement...
Recently, Two-Stream Convolutional Network has achieved remarkable performance. Especially, by capturing appearance and motion information, spatial-temporal two- stream networks bring noticeable improvement. On the other hand, dynamic image, which is a powerful representation for videos, has also been confirmed to provide complimentary information to spatial appearance. Inspired by these works, we...
In this paper, a unified deep convolutional architecture is proposed to address the problems in the person re-identification task. The proposed method adaptively learns the discriminative deep mid-level features of a person and constructs the correspondence features between an image pair in a data-driven manner. The previous Siamese structure deep learning approaches focus only on pair-wise matching...
Optical Character Recognition (OCR) in the scanned documents has been a well-studied problem in the past. However, when these characters come from the natural scenes, it becomes a much more challenging problem, as there exist many difficulties in these images, e.g., illumination variance, cluttered backgrounds, geometry distortion. In this paper, we propose to use a deep learning method that based...
Color mapping for 3D models with captured images is a classical problem in computer vision. Typically, registration between 3D model and images is assumed to be provided, otherwise corresponding points need to be labeled. For many applications, 3D model and images are acquired from different devices, since registration cannot be directly obtained, manual labeling has to be adopted. In this paper,...
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