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How to balance the speed and the quality is always a challenging issue in pedestrian detection. In this paper, we introduce the Learning model Using Privileged Information (LUPI), which can accelerate the convergence rate of learning and effectively improve the quality without sacrificing the speed. In more detail, we give the clear definition of the privileged information, which is only available...
In wilderness search and rescue missions, unmanned aerial vehicles (UAVs) may be deployed to collect high-resolution imagery which is later reviewed by a first responder. The volume of images and the altitude from which they are taken makes manually identifying potential items of interest, like clothing or other man-made material, a difficult task. For this reason, we created a program that automatically...
Obesity is prevalent worldwide including UK and Ireland, affecting all demographics. Obesity can have a detrimental affect on an individual's health, which can lead to chronic conditions. Different digital interventions have enabled users to photograph food items to be identified using different feature extraction methods. In this research, we proposed a system that allows users to draw a polygon...
Nowadays, there are many different types of mobility aids for elderly people. Nevertheless, these devices may lead to accidents, depending on the terrain where they are being used. In this paper, we present a robust ground change detector that will warn the user of potentially risky situations. Specifically, we propose a robust classification algorithm to detect ground changes based on colour histograms...
This paper addresses the problem of upper body pose estimation. The task is to detect and estimate 2D human configuration in static images for six parts: head, torso, and left-right upper and lower arms. The common approach to solve this has been the Pictorial Structure method (Felzenszwalb and Huttenlocher, 2005). We present this as a graphical model inference problem and use the loopy belief propagation...
This paper addresses the problem of person re-identification and its application to a real world scenario. We introduce a retrieval system that helps a human operator in browsing a video content. This system is designed for determining whether a given person of interest has already appeared over a network of cameras. In contrast to most of state of the art approaches we do not focus on searching the...
Road safety is influenced by the adequate placement of traffic signs. As the visibility of road signs degrades over time due to e.g. aging, vandalism or vegetation coverage, sign maintenance is required to preserve a high road safety. This is commonly performed based on inventories of traffic signs, which should be conducted periodically, as road situations may change and the visibility of signs degrades...
In Bag-of-Words-based image retrieval, the local feature could not describe the global information of an image. It produces many false matches and reduces the retrieval precision. To address this problem, this paper proposes a new method which is based on the global and local feature similarity. The global feature extracted by convolutional neural network is added to the local keypoints extracted...
This paper presents a method that integrates an effective data association with tracking persistency constraint into motion models to track pedestrians in video sequences captured by a fixed camera. Pedestrians are detected at each frame using the HOG+B/F human detector which combines HOG human detector and background subtraction technique. We impose the tracking persistency constraint into data association...
Skin detection is a key aspect of many computer vision applications including face detection, person identification, illicit content detection and other related applications. In this paper, a skin detection method is proposed combining two color spaces HSV (Hue, Saturation, Value) and YCgCr (luminance, chrominance in green, chrominance in red). The S, Cg and Cr components are used to form a hybrid...
In this paper, we introduce a framework for a system which intelligently assigns an edge detection filter to an image based only on features taken from the image. The system has four parts, the training set which consists of an image and its edge image ground truth, feature extraction, training filter creation, and system training. A prototype system of this framework is given. In the system feature...
In this paper a two stage image filtering scheme is presented. In the firest stage adaptive neuro-fuzzy system(ANFIS) based impulse noise detector is used to locate the noisy pixels and in the second stage improved vector median filter is used to provide the accurate value of the corrupt pixel. The training of the detector is accomplished by several natural images. The filtering stage changes the...
We proposed a new fast object detection architecture based on region, which consists of two stages, using manually-designed features and convolutional neural network (CNN) respectively. The first stage is generating many initial proposal windows, and then do objectness measure and ranking, to reduce the quantity of proposal windows. In this stage, we apply four manually-designed objectness features...
Challenging ground truth and standardized metrics are a mandatory requirement for the development and evaluation of computer vision algorithms. Despite the significant amount of publications on video based fire detection research it remains difficult to compare different algorithms due to the lack of common evaluation schemes and evaluation datasets. We address both of these issues by presenting a...
Rehabilitative follow-up care is important for stroke patients to regain their motor and cognitive skills. We aim to develop a robotic rehabilitation assistant for walking exercises in late stages of rehabilitation. The robotic rehab assistant is to accompany inpatients during their self-training, practicing both mobility and spatial orientation skills. To hold contact to the patient, even after temporally...
Skin detection is an essential preliminary step in many applications. Most skin detectors are color based. The distributions of skin and non-skin colors overlap, and so color cannot fully discriminate between skin and non-skin pixels. Skin detection is made more difficult by the need to be able to robustly detect skin in a wide range of illumination settings. Several color correction methods have...
Research in traffic light recognition (TLR) has stagnated compared to related computer vision areas, such as pedestrian detection and and traffic sign recognition. We focus on the detection sub-problem, since this is the most challenging problem and solving this is the key to a successful TLR system. This is done by looking at four detectors from different author groups and their reported results...
To achieve better performance of visual tracking, an improved TLD tracking algorithm was proposed. Firstly, the performance of objects detection classifiers was improved by the usage of the color attributes of objects. The accuracy of objects detector was boosted by using the color attributes of initial object, which was labeled manually. Secondly, Kalman Filter is adopted to estimate localization...
In this paper, a Binary Robust Invariant Scalable Keypoints (BRISK) based detection is utilized to facilitate the flying unmanned aerial vehicle (UAV) localization within its autonomous landing on the runway. Specifically, two target detection algorithms are proposed and developed as the BRISK-supported approach. Dataset of images and differential GPS are recorded by a ground stereo vision guidance...
Color represents an important attribute in the field of traffic sign recognition. However, when the color of the traffic sign fades or the traffic scene is collected in gray as in the case of Infrared imaging, then color based recognition systems fail. Other problems related to color are simply that different countries use different colors. Even within the European Union, colors of traffic signs are...
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