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Object Counting and Tracking are an integral part of computer-aided surveillance intelligence. In this paper, we propose an Object Counting algorithm based on region segmentation and a tracking method that works on the Kalman Filter to predict the next state of a moving object. We considered people, moving under an overhead camera as our primary targets. As a pre-processing step, we extracted foreground...
In this paper, we propose a navigation system consisting of a novel multi-sensor fusion method for calculating precise and accurate aerial coordinates and orientation, of a quadcopter in indoor and GPS-silent environments. A prototype system is developed that is composed of 2 modules: Simultanious Localization and Mapping (SLAM) system that uses Oriented FAST and rotated BRIEF (ORB) features, also...
In order to track the localizations of mobile devices in an unknown environment, this paper presents an architecture combining a monocular camera and an inertial measurement unit (IMU) in ubiquitous mobile devices. The IMU module provides acceleration and angular velocity with high-frequency, but the IMU-based motion tracking is more inclined to collapse due to the drift integration. While the vision-based...
We present a Visual Inertial Odometry system that enables the autonomous flight of Micro Aerial Vehicles in GPS denied and unstructured environments. The system relies on commercially available and affordable hardware both for sensing and computation. The algorithm runs in real time on an ARM based embedded micro-computer on-board an MAV. In experiments, we demonstrate the performance of the system...
Localization is a key capability for autonomous vehicles especially in urban scenarios. We propose the use of pole-like landmarks as primary features in these environments, as they are distinct, long-term stable and can be detected reliably with a stereo camera system. Furthermore, the resulting map representation is memory efficient, allowing for easy storage and on-line updates. The localization...
As the problem of traffic congestion is increasing day by day, there is a pressing need for the introduction of advanced system to monitor and control traffic efficiently. The analysis of traffic data collected from the camera based systems are the main method used for this purpose. The method presented here can detect vehicles, track and count them with high accuracy on videos from the intersection...
We improve uncalibrated visual servoing for multiple cameras. This moves robots towards being more effective in unstructured environments. Our approach improves performance and reliability by prioritizing data from particular cameras in the system. Adaptive filtering is used to effect this in an uncalibrated situation. Rules are introduced for ensuring positive definite covariance estimates, with...
Fine grained indoor localization is attractive for its wide usage in indoor navigation system, infrastructure management, and blooming augmented reality applications. In this paper, we propose a smartphone based indoor localization system called Plotter, providing a centimeter-grade localization service without any prior knowledge or additional devices. Leveraging the simultaneous localization and...
In this paper we focus on the problem of pedestrian detection in low visibility conditions, with infrared cameras. Widely applied, tracking is essential for driving assistance applications, providing support for removing false positives and forcing the detection of border line true positives. We propose a multiple feature and temporal based pedestrian detector for far-infrared images. Our model benefits...
This paper presents the fusion techniques for detecting and tracking the face. The proposed method combines the Viola-Jones method, the CamShift tracking, and the Kalman Filter tracking. The objective is to increase the face detection rate, while reduce the computation cost. The proposed method is implemented on a low cost embedded system based-on the Raspberry Pi module. The experimental results...
This paper presents a novel object tracking system that combines support vector machines (SVM) and Kalman filter. Objective tracking in videos is a challenging problem due to loss of information, which may be caused by varying illuminance in a scene, occlusions, similar target appearances, and so on. In this paper, we use Kalman filter to predict the dynamics of target object, so as to generate candidate...
This paper describes the process of the development and improvement of the altitude and vertical velocity estimation algorithm. The previous method was developed by authors two years back. After a diagnosis of pressure temperature drift caused by the main IMU, the additional barometric sensor was introduced. Based on readings from this reference component, three main modifications were developed to...
Real-time pose estimation is a challenge in multi-camera vision system due to the demand of rapid response, high accuracy and robustness. Although some works based on multi-camera have been proposed, few works have regarded multi-camera as a fixed integration, which is easier to apply in real robotic application than eye-in-hand/eye-to-hand configuration. This paper proposes a novel Kalman-filter-based...
This study demonstrates computational methods for the automatic detection and tracking of fish from video sequences. The research in this subject is very important especially in fish farming companies and for nature protection around the world. The process of automated control and counting of individual species of fish has a supportive contribution both in the nature conservation and in the food industry...
There has been a surge of interest in event-triggered control in recent years, and many event-triggered control methods are now available in the literature. As the theory matures, there is a need to experimentally validate and test these methods in applications of interest. In this paper, we extend and experimentally validate an event-triggered control strategy presented in [1] for the remote point...
The visual tracking of an object is a well-known problem, and it involves many fields of applications. Often a single sensor, the camera, could not provide enough information in order to track the whole object trajectory due to a low updating rate; therefore a multi-sensor system, based also on inertial measurements, could be necessary to improve the tracking accuracy. This leads to the fundamental...
Using fish behavior to reflect changes of water quality and aim at water quality warning is currently a popular topic of environmental monitoring. The fish tracking technology with occlusion is the basis for the analysis of fish school behavior, and only tracking each individual fish accurately in the shoal can get the exact quantitative analysis of their feature. In this paper, we design the data...
Using Augmented Reality (AR) could offer stimuli to rehabilitation from neuro-motor disorders, since the patient can be aided in a better known reality than Virtual Reality (VR). The main goal for an AR system is to achieve a good quality of tracking the real object to align with virtual contents. Often a single sensor could not provide enough information to that end due to a low updating rate; therefore...
With more and more high rise buildings in modern cities, people flow and occupancy estimation has gained lots of attention in recent years. Most previous works on this topic are based on the Kalman filter (KF) due to its high efficiency. However, the Kalman filter requires good people flow models which are usually hard to get due to the complexity of people behavior. People simulation softwares such...
In video surveillance to count the number of people walking through a corridor or door people counting is used. Counting persons passing through supervised area is important issue of this domain. System of people counting is important for security application (such as in the situation of an evacuation, it is vital to know how many people are present inside the surveillance area at any given time),...
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