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Hand Gesture Recognition is completed on top-view hand images observed by a Time of Flight(ToF) camera in a car. The work attempts to solve two important problems of touchless interactions inside a car. First, low latency identification of the gestures which are unobtrusive for the driver. Second, reducing the labelled data required to train learning based solutions, this is particularly important...
To robustly estimate the pose, classical methods assume some geometrical and temporal assumptions (SfM: Structure from Motion, SLAM: Simultaneous Localization and mapping). These approaches take a pair of images as input and establish correspondences based on global strategy (using the whole image information) or sparse strategy (using key-points features). These correspondences allow solving a set...
Automatic License Plate Recognition (ALPR) is an important task with many applications in Intelligent Transportation and Surveillance systems. As in other computer vision tasks, Deep Learning (DL) methods have been recently applied in the context of ALPR, focusing on country-specific plates, such as American or European, Chinese, Indian and Korean. However, either they are not a complete DL-ALPR pipeline,...
In this paper we present a skeleton-free Kinect system to estimate body mass index (BMI) of human bodies. Unlike other systems in the literature, the proposed system does not require a scale to measure the weight. The weight of observed subjects are estimated using body surface area (BSA) regression. The proposed system employs the state-of-the-art deep residual network to extract meaningful features...
This paper presents a neural-network-based approach for the detection of misplaced and missing regions in images. The main objective of this project is to develop an intelligent system that can identify a misplaced or missing region of a tested image. The system can be used to detect misplaced and missing components of printed circuit boards during the manufacturing process. Jigsaw puzzle pieces can...
Building a human-computer interactive parachute simulator is an efficient way to avoid the high risk and high cost of field parachute training. In this paper, a novel dynamic recognition and simulation approach of parachute training is developed. Firstly we process the skeletal data acquired by Kinect and enforce the indication of the trainees' parachute posture, where principle component analysis...
With the development of unmanned aerial vehicles (UAVs) and the relevant techniques, UAVs become common and popular for civilian applications such as remote sensing tasks. The reason is because they are cheap, flexible, and easy to set up. Car park occupancy analysis is important for authorities to make decisions on the design, plan and management of car parks. To have a quick knowledge of current...
In this paper, we present a tracking system to estimate the position of a surgical instrument used in minimally invasive spine surgeries for training. The purpose of our system is to get the information about movements and surgeons skills during the training. The system uses four infrared markers embedded on the surgical instrument of common used. At least two Wii Remote Control is needed for calculating...
Recently, in the field of speech processing, I-Vector modeling has been appealed a great deal of interest. I-Vector has shown its benefits in modeling of intra and inter-domain variabilities to a single low dimension space for speaker identification tasks. This paper presents the usage of I-Vector in camera identification as a new approach in image forensics domain. In our approach, image texture...
In this paper, a system to aid the visually impaired by providing contextual information of the surroundings using 360° view camera combined with deep learning is proposed. The system uses a 360° view camera with a mobile device to capture surrounding scene information and provide contextual information to the user in the form of audio. The scene information from the spherical camera feed is classified...
Body surface area is an important measure in many clinical trials. It is a critical parameter that is used in estimating radiation and substance doses for human trials. Traditionally, these trials relied on skin-fold tests which are very invasive and uncomfortable to the subjects. In this paper we present a skeleton-free Kinect system to estimate body surface area of human bodies. The proposed system...
This paper presents the first photometric registration pipeline for Mixed Reality based on high quality illumination estimation using convolutional neural networks (CNNs). For easy adaptation and deployment of the system, we train the CNNs using purely synthetic images and apply them to real image data. To keep the pipeline accurate and efficient, we propose to fuse the light estimation results from...
In this paper, we present a method to estimate abstract parameters of high definition (HD) maps from sensor data. Parameters we estimate include the distance from ego-vehicle to road boundary, orientation of the ego-vehicle with respect to lanes, number of lanes, and street type. Our method is realized as a Convolutional Neural Network (CNN) that takes pre-processed sensor information in the form...
This paper proposes a new optical camouflage system that uses RGB-D cameras, for acquiring point cloud of background scene, and tracking observers' eyes. This system enables a user to conceal an object located behind a display that surrounded by 3D objects. If we considered here the tracked point of observer's eyes is a light source, the system will work on estimating shadow shape of the display device...
Argumentation mining aims at automatically extracting the premises-claim discourse structures in natural language texts. There is a great demand for argumentation corpora for customer reviews. However, due to the controversial nature of the argumentation annotation task, there exist very few large-scale argumentation corpora for customer reviews. In this work, we novelly use the crowdsourcing technique...
Despite a rapid rise in the quality of built-in smartphone cameras, their physical limitations – small sensor size, compact lenses and the lack of specific hardware, – impede them to achieve the quality results of DSLR cameras. In this work we present an end-to-end deep learning approach that bridges this gap by translating ordinary photos into DSLR-quality images. We propose learning the translation...
While recovery of hyperspectral signals from natural RGB images has been a recent subject of exploration, little to no consideration has been given to the camera response profiles used in the recovery process. In this paper we demonstrate that optimal selection of camera response filters may improve hyperspectral estimation accuracy by over 33%, emphasizing the importance of considering and selecting...
Parsing urban scene images benefits many applications, especially self-driving. Most of the current solutions employ generic image parsing models that treat all scales and locations in the images equally and do not consider the geometry property of car-captured urban scene images. Thus, they suffer from heterogeneous object scales caused by perspective projection of cameras on actual scenes and inevitably...
An emerging problem in computer vision is the reconstruction of 3D shape and pose of an object from a single image. Hitherto, the problem has been addressed through the application of canonical deep learning methods to regress from the image directly to the 3D shape and pose labels. These approaches, however, are problematic from two perspectives. First, they are minimizing the error between 3D shapes...
Person re-identification (Re-ID) is an important problem in video surveillance, aiming to match pedestrian images across camera views. Currently, most works focus on RGB-based Re-ID. However, in some applications, RGB images are not suitable, e.g. in a dark environment or at night. Infrared (IR) imaging becomes necessary in many visual systems. To that end, matching RGB images with infrared images...
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