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In this work, using a new set of color features in the field of computer vision and image processing which are inspired by the work of artists, we try to classify different subjective properties of paintings, including aesthetic quality, beauty, and liking of color. We then investigate if observers have individual tastes and opinions when evaluating different properties of artworks. The extracted...
In 3D object recognition, local feature-based recognition is known to be robust against occlusion and clutter. Local feature estimation requires feature correspondences, including feature extraction and matching. Feature extraction is normally a two-stage process that estimates keypoints and keypoint descriptors, and existing studies show repeatability to be a good indicator of keypoint feature detector...
Visual tracking is a very challenging problem in computer vision as the performance of a tracking algorithm may be degraded due to many challenging issues in the scenes, such as illumination change, deformation, and background clutter. So far no algorithms can handle all these challenging issues. Recently, it has been shown that correlation filters can be implemented efficiently and, with suitable...
A novel composite approach through integration of variational optical flow and surface splines is presented to obtain sub-pixel accurate dense disparity map for remotely sensed stereo image pair. It is well known that, surface splines handle geometric distortion very well. The performance of surface splines for dense correspondence can be significantly improved by the reliable control points, but...
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...
Image annotation methods construct a Tag distance matrix, which entries show the relevancy of tags for each test image. More accuracy in calculating this matrix provides better annotation results. The aim of our two methods is to improve the accuracy of the Tag distance matrix using the class information already available in most datasets. If the class information is not available, extracting important...
Precision agriculture has enabled significant progress in improving yield outcomes for farmers. Recent progress in sensing and perception promises to further enhance the use of precision agriculture by allowing the detection of plant diseases and pests. When coupled with robotics methods for spatial localisation, early detection of plant diseases will al- low farmers to respond in a timely and localised...
Due to the diversity of food types and the slight differences between different dishes, the genre of food images becomes a new challenge in the field of computer vision. To tackle this problem, recent efforts are focusing on designing hand-crafted features or extracting features automatically by using deep convolutional neural network. Although these methods have reported a series of success, their...
In recent years, remarkable breakthrough has been achieved in person re-identification (Re-ID). However most methods are only tested in the closed-world setting where the probe person is assumed to be one of the gallery people. In this paper, we tackle a more realistic problem, open-world Re-ID, which requires to find out whether the probe person is among the gallery or not, and if so, who he is....
In typical applications, chromatic indices are calculated as linear combinations of the normalized r-, g- and b-channels and used as features for a later classification based on chromatic appearance. But the variety of indices used in the literature is very limited. Furthermore is the choice of which index to use justified either empirically, based on false mathematical assumptions or not justified...
Pedestrian trajectory prediction is important in various applications such as driverless vehicles, social robots, intelligent tracking systems and space planning. Existing methods focus on analysing the influence of neighbours but ignore the effect of the intended destinations of pedestrians which also plays a key role in route planning. In this paper, we propose a novel two- stage trajectory prediction...
We present a novel data set made up of omnidirectional video of multiple objects whose centroid positions are annotated automatically. Omnidirectional vision is an active field of research focused on the use of spherical imagery in video analysis and scene understanding, involving tasks such as object detection, tracking and recognition. Our goal is to provide a large and consistently annotated video...
Accurate vessel segmentation is a tough task for various medical images applications especially the segmentation of retinal images vessels. A computerised algorithm is required for analysing the progress of eye diseases. A variety of computerised retinal segmentation methods have been proposed but almost all methods to date show low sensitivity for narrowly low contrast vessels. We propose a new retinal...
Salient object detection has been greatly boosted thanks to the deep convolutional neural networks (CNN), especially fully convolutional neural networks (FCN). Nowadays, it is possible to train an end-to-end deep model for salient object detection. However, the diverse scales of salient objects still pose major challenges for these state-of-the-art methods. In this paper, we investigate how different...
This paper proposes a new pylon detection technique from point cloud data. Two masks are created from the non-ground points that mainly represent trees and power line components. The first mask is the power line mask Mₘ, which contains the power line components and trees and where successive pylons are found connected with wires. The second mask is the pylon mask Mₚ, where successive pylons are found...
We propose an action parsing algorithm to parse a video sequence containing an unknown number of actions into its action segments. We argue that context information, particularly the temporal information about other actions in the video sequence, is valuable for action segmentation. The proposed parsing algorithm temporally segments the video sequence into action segments. The optimal temporal segmentation...
This research proposed an automatic student identification and verification system utilising off-line Thai name components. The Thai name components consist of first and last names. Dense texture-based feature descriptors were able to yield encouraging results when applied to different handwritten text recognition scenarios. As a result, the authors employed such features in investigating their performance...
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...
Skin segmentation, which involves detecting human skin areas in an image, is an important process for skin disease analysis. The aim of this paper is to identify the skin regions in a newly collected set of psoriasis images. For this purpose, we present a committee of machine learning (ML) classifiers. A psoriasis training set is first collected by using pixel values in five different color spaces...
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