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Swarms of drones are increasingly being requested to carry out missions that cannot be completed by single drones. Particularly in the field of civil security, strong needs emerge in terms of surveillance and observation of hostile, distant or extended areas. Currently, existing solutions do not meet this demand, as they are generally based on too heavy infrastructures or over-processing, without...
In this paper, we propose a multi-object tracking and reconstruction approach through measurement-level fusion of LiDAR and camera. The proposed method, regardless of object class, estimates 3D motion and structure for all rigid obstacles. Using an intermediate surface representation, measurements from both sensors are processed within a joint framework. We combine optical flow, surface reconstruction,...
Unmanned aerial vehicles (UAVs) are rapidly increasing in popularity. Despite attempts at regulation, stopping small, Class 1 (typically hobby-grade) UAVs from entering protected or sensitive airspace is an unsolved problem. Many companies and researchers offer a piece of a solution, but as of this writing, there is no publicly available, feasible, end-to-end solution. Ultimately, what is needed is...
Visual (V) surveillance systems are extensively deployed and becoming the largest source of big data. On the other hand, electronic (E) data also plays an important role in surveillance and its amount increases explosively with the ubiquity of mobile devices. One of the major problems in surveillance is to determine human objects' identities among different surveillance scenes. Traditional way of...
Portable devices are nowadays largely used among people. These devices have a lot of potential in aiding visually impaired people on a daily basis. This paper presents an android application for smartphone, especially made to assist these persons. The application uses MEMS sensors from a smartphone and also the information received from a few external sensorial modules. The hardware modules form together...
Environment sensing is an essential property for autonomous cars. With the help of sensors, nearby objects can be detected and localized. Furthermore, the creation of an accurate model of the surroundings is crucial for high-level planning. In this paper, we focus on vehicle detection based on stereo camera images. While stereoscopic computer vision is applied to localize objects in the environment,...
This paper proposes the concept of drones capable of functioning as “Co-Archaeologists” that can map large caves and enter dangerous or hard-to-reach spaces. Using RGB-D data collected by drones, we will be able to produce accurate 3D models and semantic maps with proper lighting co-supervised by human archaeologists. This is going to be a major advance in archaeological practice, which can accelerate...
In this paper, a fully-autonomous quadrotor aerial robot for solving the different missions proposed in the 2016 International Micro Air Vehicle (IMAV) Indoor Competition is presented. The missions proposed in the IMAV 2016 competition involve the execution of high-level missions such as entering and exiting a building, exploring an unknown indoor environment, recognizing and interacting with objects,...
Current state-of-the-art vision-based sense and avoid systems based on morphological and hidden Markov model filtering require the manual selection of static (timeinvariant) detection thresholds. Manually selecting suitable static detection thresholds is challenging (and currently requires highly trained operators) because it involves balancing tradeoffs between detection and false alarm performance...
Unmanned Aerial Vehicles (UAVs) with high level autonomous navigation capabilities are a hot topic both in industry and academia due to their numerous applications. However, autonomous navigation algorithms are demanding from the computational standpoint, and it is very challenging to run them on-board of nano-scale UAVs (i.e., few centimeters of diameter) because of the limited capabilities of their...
Situational awareness involves the timely acquisition of knowledge about real-world events, distillation of those events into higher-level conceptual constructs, and their synthesis into a coherent context-sensitive view. We explore how convergent trends in video sensing, crowd sourcing and edge computing can be harnessed to create a shared real-time information system for situational awareness in...
Unmanned Aerial Vehicles (UAVs) exhibit great agility and usually require a trained pilot to operate them, while being restricted to line-of-sight range. This prevents their wide introduction in applications such as inspection for disaster scenarios. Our goal is to enable rescue teams untrained in piloting to teleoperate a UAV as an aid to their mission, while being able to focus on the task at hand...
For advanced driver assistance system (ADAS) which are related to risk assessment or collision avoidance, predicting object vehicle's path is needed beyond the precise and reliable sensor data to improve the performance of path prediction. This paper proposes an object vehicle path prediction method using parametric interpolation. To obtain a precise and reliable sensor data, multirate sensor data...
This paper addresses the autonomous landing of an unmanned aerial vehicle (UAV) on a ground vehicle. Unlike most of the previous research on autonomous UAV landing that used onboard sensors mounted on the UAV, this study suggests using a lidar mounted on a ground vehicle for lidar-guided landing. To estimate the relative position of the UAV with respect to the landing platform, a clustering algorithm...
This paper presents a study of near collision course engagements between a Cessna 172R aircraft and a ScanEagle UAV carrying a custom built vision-based sense-and- avoid system. Vision-based systems are an attractive solution for the sense-and-avoid problem because of size, weight and power considerations. We present post flight test analysis that shows our detection system successfully detecting...
In this work, we present a method for lane-precise localization in downtown scenarios based on a geometric map and sensors present in a current production vehicle. In detail, we use low-cost GPS, odometry, lane-marking detection based on a camera, objects detected by a front radar, and events from a blind spot monitoring system. The proposed combined weight update and sampling step in a particle filter...
In this paper, the problem of queue in convenient stores is considered. We propose a low cost automatic queue length monitoring system by using an Internet-of-Things (IoT) platform. This system can detect the length of queue and the number of people that enqueue and leave the queue. If the length of queue is critical, the system will alert to staff via LINE Notify. Experimental results indicate that...
In all the researches in wireless sensor networks, cameras are increasingly utilized for their surveillance capabilities. In this paper, we elaborately discuss about the problem of Full-View Barrier Coverage with Rotatable Camera Sensors (FBR), including weakly and strongly connected versions. FBR is proven to be NP-hard in this paper by reducing Group Steiner Tree problem to it. Our goal is to reduce...
Recen% developed near W-photosensors are currently adopted in those applications where high sensitivity and good imaging capabilities are required, especially in fields such as astroparticle physics and medical imaging. An example of such applications is the camera of the Schwarzschild Couder Medium Size Telescope prototype (pSCT) which is in construction within the Cherenkov Telescope Array experiment...
Detecting students' attention in class provides key information to teachers to capture and retain students' attention. Traditionally, such information is collected manually by human observers. Wearable devices, which have received a lot of attention recently, are rarely discussed in this field. In view of this, we propose a multimodal system which integrates a head-motion module, a pen-motion module,...
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