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Although light field data provides abundant cues for depth estimation, light field depth estimation suffers from occlusion and uncertain edges. In this paper, we propose occlusion robust light field depth estimation using segmentation guided bilateral filtering. First, we calculate refocused images from light field data using digital refocusing. Second, we perform support vector machines (SVM) classification...
This paper describes a new prototype system for detecting the demeanor of patients in emergency situations using the Intel RealSense camera system [1]. It describes how machine learning, a support vector machine (SVM) and the RealSense facial detection system can be used to track patient demeanour for pain monitoring. In a lab setting, the application has been trained to detect four different intensities...
Hand gesture recognition is highly valued for its potential applications in contactless human-computer interaction (HCI). Aiming at the problem that the gesture recognition system based on ordinary camera is susceptible to different lighting conditions and complex background environment, an improved algorithm based on depth image for fingertip detection and gesture recognition is proposed. Firstly,...
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...
The analysis of human motion as a clinical tool can bring many benefits such as the early detection of disease and the monitoring of recovery, so in turn helping people to lead independent lives. However, it is currently under used. Developments in depth cameras, such as Kinect, have opened up the use of motion analysis in settings such as GP surgeries, care homes and private homes. To provide an...
Classification of human actions is very challenging and important in many video-based applications. Two common features, i.e., the hand-crafted and the deep-learned ones are usually adopted for video representation and have been proven to be effective in many famous datasets in the literature. However, the hand-crafted feature lacks the ability to detect the discriminative and semantic features and...
UAVs (Unmanned Aerial Vehicles) have been widely used in power line inspections, but low autonomous cruise capacity of UAVs requires strict condition for operators and site while landing during UAV power line inspections. This paper presents an autonomous landing control technique for UAVs when charging at the electric towers based on vision positioning method. The proposed system consists of three...
This paper presents a real-time vision based robot teleoperation system that consists of a three-dimensional (3D) vision subsystem and a slave robot which are connected by LAN. The vision subsystem utilizes an Asus Xtion Pro Live camera to get the 3D data of the operation scene. The vision system is used to determine the position and orientation of a four-ball feature frame held by the operator. Then...
Many existing person re-identification (PRID) methods typically attempt to train a faithful global metric offline to cover the enormous visual appearance variations, so as to directly use it online on various probes for identity match- ing. However, their need for a huge set of positive training pairs is very demanding in practice. In contrast to these methods, this paper advocates a different paradigm:...
This work proposes an approach for performing Human-Robot Cooperation (HRC) tasks by integrating a Brain Computer Interface (BCI) with a robotic manipulator. In detail, the user can select one among six different objects via BCI, which analyzes the P300 signals generated by the brain when the images of the selectable objects appear on the screen. Then, the selected object is recognized by a Support...
An approach for object detection in depth images based on local and global convexity is presented. The approach consists of three steps: image segmentation into planar patches, greedy planar patch aggregation based on local convexity and segment grouping based on global convexity. The proposed approach improves upon existing similar methods, which use convexity as a cue for object detection, by detecting...
This paper presents a pedestrian detection system with enhanced object segmentation procedure working on a far infrared (FIR) video. To make the object detection more accurate on the FIR images, we propose an enhanced segmentation procedure with two thresholds and the region enlargement. This combination allowed a significant reduction of the region of interests (ROIs) for further processing. Experiments...
The growing interest in recent years for gender recognition from face images is mainly attributable to the wide range of possible applications that can be used for commercial and marketing purposes. It is desirable that such algorithms process high resolution video frames acquired by using surveillance cameras in real-time. To the best of our knowledge, however, there are no studies which analyze...
On the aged society coming soon, many studies have explored homecare technologies. In this work, the activities at home are captured by a panoramic camera located at the center of a living room, and then analyzed and classified into standing, walking, sitting, falling, and watching television. First, the background subtraction scheme accompanied with shadow removal, and morphological operators of...
This paper describes the challenge of real-time tumor tissue identification dealt with by the HypErspectraL Imaging Cancer Detection (HELICoiD) European project. This project was funded by the Research Executive Agency, through the Future and Emerging Technologies (FET-Open) programme, under the 7th Framework Programme of the European Union. It involved four universities, three industrial partners...
Haar-Cascade classifier method has been applied to detect the presence of a human on the thermal image. The evaluation was done on the performance of detection, represented by its precision and recall values. The thermal camera images were varied to obtain comprehensive results, which covered the distance of the object from the camera, the angle of the camera to the object, the number of objects,...
Pedestrian detection is considered as an active area of research and the advent of autonomous vehicles for a smarter mobility has spearheaded the research in this field. In this paper, design of a real-time pedestrian detection system for autonomous vehicles is proposed and its performance is evaluated using images from standard datasets as well as realtime video input. The proposed system is designed...
Behavior or human action recognition is one hot research topic in real-time video surveillance system. Dangerous accidents consist of dangerous actions by one or more persons. Thus, action recognition is very important for dangerous accident recognition. If videos captured by public cameras especially dangerous actions related videos can be processed and analyzed immediately to provide an early and...
The robots in warehouse have boosted the efficiency and economic benefits of the logistic industrial chain. This paper provides a deep learning, single-camera-based solution to navigate vehicles in warehouse. Firstly we train a Faster R-CNN model to detect shelf-legs and tags in the captured image. To position the localized objects into the world coordinate, we then present a precise Inverse Perspective...
Periocular characteristics has gained substantial importance in recent times to supplement the performance of facial biometrics or as a stand-alone characteristics. While most of the current biometric systems for authentication or surveillance operate either in NIR spectrum or visible spectrum, the ocular information can be well utilized if a comparison of images from different spectra has to be conducted...
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