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In this paper, a novel artificial potential function is proposed for planning the path of a robotic sensor in a partially observed environment containing multiple obstacles and multiple targets. The sensor planning problem considered in this paper consists of planning the motion of a robot with an on-board sensor that is deployed in order to support a sensing objective, such as, target detection and...
Detection and analysis of trajectories are effective for providing services to pedestrians in public spaces. We have proposed a method to detect moving objects from a monocular image sequence with a normal mixture model. However, the method cannot accommodate a changing number of moving objects. As described herein, to overcome this shortcoming, we proposed two algorithms for counting number of moving...
Sleep scheduling protocols are widely used in wireless sensor networks for saving energy in sensor nodes. However, without considering the special requirements of object tracking, conventional sleep scheduling protocols may lead to intolerable degradation of tracking qualities when they are used in object tracking applications. To handle this problem, sleep scheduling protocols tailed for object tracking...
Detection of license plate is an important process in intelligent transportation systems before license plate recognition. In this paper, we proposed an autonomous license plate detection system with computer vision instead of sensors. Using characteristics of dynamic images, our system rapidly identifies the license plate region. The system consists of two subsystems: car detection subsystem and...
In this paper, a robust and efficient approach for multicamera human tracking is presented. The approach is integrated in an experimental surveillance system, based on a camera network with a task-oriented architecture. At sensor level, image processing algorithms are applied for object detection and feature extraction. Additionally, for each object that is to be tracked, an agent-based multi-sensor...
Object detection by visual sensors is a critical component of surveillance systems and has many challenging issues. This paper addresses enhancement of object detection with multiple visual sensors. The detection enhancement we introduce is to recover missed object detection given partially detected objects among multiple visual sensors. Once an object is detected by one or more visual sensors, the...
Driving assistance systems provide either safety or comfort functions. Such systems must evaluate the state of the world and take necessary actions. A preliminary step for evaluating the state of the world is to detect, track and classify scene objects. The classification step becomes especially important in complex urban traffic scenarios. In such scenarios the sensors of choice are vision based,...
Environment monitoring is an important class of wireless sensor networks applications. A traditional way for such applications is to deploy sensors all over a region and always aim to cover as more area as possible. However, this way is not only a great waste of money and recourses but also unnecessary and unrealistic. It also invokes many data collisions and brings serious burden to the network protocols...
A sensor uses nearby sensors to collect information and sends the information to sinks. Then, the sink forwards this collected information to users. However, if the purpose of these sensors is not to collect general data but to sense the movement of movement objects, it is difficult to sense fast moving objects with a clustering technique, which is used to collect general data. In this paper we propose...
It is important to extract ROI (Region of Interest) based on vision image processing in intelligent transportation system. A simple and novel approach is proposed to extract the RIO in transportation scene images. Firstly, a simple method is used to preprocess the input images; Secondly, interest pixels extraction function is defined to detect all the interest pixels from scene image using adaptive...
The increasing availability of remote-sensing images, acquired periodically by satellite sensors on the same geographical area, makes it extremely interesting to develop monitoring systems capable of automatically producing and regularly updating forest-cover maps of the considered site. In this paper, we designed and developed new object-based change detection algorithms, which are aimed at updating...
In many driver assistance systems and autonomous driving applications, both LIDAR and computer vision (CV) sensors are often used to detect vehicles. LIDAR provides excellent range information to different objects. However, it is difficult to recognize these objects as vehicles from range information alone. On the other hand, computer vision imagery allows for better recognition, but does not provide...
Path coverage is one of the applications of wireless sensor networks where the network is responsible for monitoring a path and detecting any object that crosses it. Here, we study the path coverage of a randomly deployed wireless sensor network when the path length and number of sensors are finite (thus the widely used Boolean model is not applicable). More specifically, we find the probability of...
Present object detection methods working on 3D range data are so far either optimized for unstructured offroad environments or flat urban environments. We present a fast algorithm able to deal with tremendous amounts of 3D lidar measurements. It uses a graph-based approach to segment ground and objects from 3D lidar scans using a novel unified, generic criterion based on local convexity measures....
Minimizing the number of computations a low-power device makes is important to achieve long battery life. In this paper we present a framework for a low-power device to minimize the number of calculations needed to detect and classify simple activities of daily living such as sitting, standing, walking, reaching, and eating. This technique uses wavelet analysis as part of the feature set extracted...
This paper presents a new method for extracting object edges from range images obtained by a 3D range imaging sensor the SwissRanger SR-3000. In range image preprocessing stage, the method enhances object edges by using surface normal information; and it employs the Hough Transform to detect straight line features in the Normal-Enhanced Range Image (NERI). Due to the noise in the sensor's range data,...
The project DEKO (Detection of artificial objects in sea areas) is integrated in the DeMarine-Security project and focuses on the detection and classification of ships and off shore artificial objects relying on TerraSAR-X as well as on RapidEye optical images. The DEKO project has been started in Mai 2008. The main expected outcomes of the DEKO project are 1/ the definition of concepts for GMES downstream...
This paper proposed a simple and novel approach for on-road object detection based on vision. Firstly, a simple method is applied to detect the interest pixels of object in images by the defined interest pixels function and a single strategy is applied to reduce the redundant computation in the process of computation gray mean of pixels in squared window; Secondly, all the detected interest pixels...
Variation in the number of targets and sensors needs to be addressed in any realistic sensor system. Targets may come in or out of a region or may suddenly stop emitting detectable signal. Sensors can be subject to failure for many reasons. We derive a tracking algorithm with a model that includes these variations using random finite set theory (RFST). RFST is a generalization of standard probability...
In ITS (intelligent transportation system), on-road object detection algorithm is one of the most important research fields and obstacle segmentation is a key factor in obstacle detection approaches. In this paper, a simple and fast segmentation approach is proposed for on-road object in ITS. Firstly, a simple method is applied to detect the interest pixels in the transportation scene images by the...
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