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We propose a novel middle level estimation of traffic scenes: Collision Risk Rating (CRR). Given a video sequence from a dashboard camera as input, the objective is to estimate a rate that describes "how likely a collision could happen". CRR's problem setting is similar to that of video classification, but it is more complicated and requires rich feature representations to capture the different...
In this work we discuss an efficient strategy for reducing the negative impact of non-uniform illumination to panoramic image quality by proposing an adaptive correction algorithm based on the improved Bilateral Gamma function. Firstly the illumination component is extracted by a fast image guided filter. Then an improved bilateral Gamma function fed by the distribution characteristics of illumination...
Video Summarization is a computer-based technique to generate a shorter version of the original long video for memory management and information retrieval. The existing method for video summarization applies affective (the state of excitement, interestingness, and panic) level of a viewer captured by Electroencephalography (EEG) while watching a video. The traditional methods for extracting features...
Classification of Alzheimer 's disease (AD) from normal control (NC) is important for disease abnormality identification and intervention. The current study focused on distinguishing AD from NC based on the multi-feature kernel supervised within- class-similarity discriminative dictionary learning algorithm (MKSCDDL) we introduced previously, which has been derived outperformance in face recognition...
The use of autonomous drones in industrial inspection is gaining momentum with improvements in hardware and control. Considering the availability of historical data as drones gather information by regular sorties, a new opportunity for change detection is emerging for inspection and maintenance. In this paper, we propose a visual change detection framework using multi- scale super pixel approach....
The bone age of a child indicates the skeletal and biological maturity of an individual. The most commonly applied clinical methods for Bone Age Assessment (BAA) are based on the visual examination of ossification of individual bones in radiographs of the left hand and the wrist by comparing with standard hand atlas. This kind of method is highly subjective and the performance extremely depends on...
Accurate early lung cancer detection is essential towards precision oncology and would effectively improve the patients' survival rate. In this work, we explore the lung cancer early detection capacity by learning from deep spatial lung features. A 3D CNN network architecture is constructed with segmented CT lung volumes as training and testing samples. The new model extracts and projects 3D features...
There is a continuous rise of the number of trains' passengers to transport, therefore a densification of traffic is studied. For safety reasons, it becomes necessary to know the wheel-rail contact condition, in traffic, as it affects driving variables as adherence. The latest determines passenger's safety and the proper functioning of train equipment but it is often deteriorated due to recurrent...
State of the art video compression techniques use the motion model to approximate geometric boundaries of moving objects where motion discontinuities occur. Motion hints based inter- frame prediction paradigm moves away from this redundant approach and employs an innovative framework consisting of motion hint fields that are continuous and invertible, at least, over their respective domains. However,...
Convolutional Neural Networks (CNN) have brought a revolutionary improvement to image analysis, especially in the image classification field. The technique of natural image classification using the CNN method has been deliberately utilized for medical image classification with some advanced engineering. However, so far in most of the cases CNN model classifies images based on global features extraction...
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...
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...
A lighting system and method has been developed which has shown in testing to allow quality images to be obtained that are free from two particular problems, specular reflections on the subject, and light intensity variation. These problems both diminish the ability to compare objects for attributes such as colour variation, edges, contours, and many other features. The system developed eliminates...
Deep learning based hyperspectral image (HSI) classification have recently shown promising performance. However, complex network architecture, tedious training process and effective utilization of spatial/contextual information in deep network limits the application and performance of deep learning. In this paper, for an effective spectral-spatial feature extraction , an improved deep network, spatial...
Small infrared target detection in complex backgrounds is a challenging task. Due to dynamic background clutter and low signal-to-clutter ratio, most conventional methods fail to produce satisfactory results. In this paper, an effective spatial and temporal filter is proposed. The spatial filter is used to remove cloud edge, and the temporal filter is used to remove point-like background clutter....
Current traffic monitoring is limited by the small coverage of camera surveillance systems, for example, a specific area around one road intersection. Satellite high definition videos are becoming available which can provide videos over several squared kilometers. Thus, these videos introduce new possibilities for better traffic control and management. However, parallax motions caused by the movements...
Facial micro-expression refers to split-second muscle changes in the face, indicating that a person is either consciously or unconsciously suppressing their true emotions and even mental health. Therefore, micro-expression recognition attracts increasing research efforts in both fields of psychology and computer vision. Existing research on micro-expression recognition has mainly used hand-crafted...
Tamura features are based on human visual perception and have huge potential in image representation. Conventional Tamura features only work on homogeneous texture images and perform poor on generic images. Therefore, many researchers attempt to improve Tamura features and most of the improvements are based on histogram based representation. Kernel descriptors have been shown to outperform existing...
Automated image stylization to create artistically pleasing images from ordinary photographs is an interesting and useful task in computer vision. Therefore, several automated styling methods have been developed using powerful Deep Neural Network (DNN) features. They typically use a carefully constructed joint loss function to separately consider the similarities between a proposed output and the...
Convolutional neural network (CNN) has drawn increasing interest in visual tracking, among which fully-convolutional Siamese network based method (SiamFC) is quite popular due to its competitive performance in both precision and efficiency. Generally, SiamFC captures robust semantics from high-level features in the last layer but ignores detailed spatial features in earlier layers, thus tending to...
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