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Global motion estimation is an important task for video stabilization. Since the global motion is heavily related to the motion of the background (BG), the moving foreground (FG) objects can cause inaccurate global motion estimation. In this paper, we propose a robust global motion estimation method for video stabilization. The proposed method iteratively finds the feature points (FPs) in the BG and...
For navigating automatic forklift, we proposed an method for locating of the forklift. To improve efficiently of image processing and robust of object identification, the color image is transformed from RGB space into HSV and YUV space. Afterwards, we find out the mid-point of the pallets, calculate position of pallets relative to forklift by camera space model which builds the relationship between...
In this paper we present an innovative technique to tackle the problem of automatic road sign detection and tracking using an on-board stereo camera. It involves a continuous 3D analysis of the road sign during the whole tracking process. Firstly, a color and appearance based model is applied to generate road sign candidates in both stereo images. A sparse disparity map between the left and right...
Automatic processing of videos coming from small UAVs offers high potential for advanced surveillance applications but is also very challenging. These challenges include camera motion, high object distance, varying object background, multiple objects near to each other, weak signal-to-noise-ratio (SNR), or compression artifacts. In this paper, a video processing chain for detection, segmentation,...
Robust and lightweight detection of alert signals of front vehicle, such as turn signals and brake lights, is extremely critical, especially in autonomous vehicle applications. Even with cars that are driven by human beings, automatic detection of these signals can aid in the prevention of otherwise deadly accidents. This paper presents a novel, robust and lightweight algorithm for detecting brake...
Estimation of a object pose from camera is a well-developing topic in computer vision. In theory, the pose from a calibrated camera can be uniquely determined. But in practice, most of the real-time pose estimation algorithms suffer from pose ambiguity due to low accuracy of the target object. We think that pose ambiguity¡Xtwo distinct local minima of the according error function¡Xexist because of...
Advanced Rider Assistance Systems (ARAS) for powered two-wheelers improve driving behaviour and safety. Further developments of intelligent vehicles will also include video-based systems, which are successfully deployed in cars. Porting such modules to motorcycles, the camera pose has to be taken into account, as e. g. large roll angles produce significant variations in the recorded images. Therefore,...
This paper presents a real time monocular EKF SLAM process that uses only Cartesian defined landmarks. This representation is easy to handle, light and consequently fast. However, it is prone to linearization errors which can cause the filter to diverge. Here, we will first clearly identify and explain when those problems take place. Then, a solution, able to reduce or avoid the errors involved by...
In this paper a novel spline-based multi-lane detection and tracking system is proposed. Reliable lane detection and tracking is an important component of lane departure warning systems, lane keeping support systems or lane change assistance systems. The major novelty of the proposed approach is the usage of the so-called Catmull-Rom spline in combination with the extended Kalman filter tracking....
Stereo visual odometry and dense scene reconstruction depend critically on accurate calibration of the extrinsic (relative) stereo camera poses. We present an algorithm for continuous, online stereo extrinsic re-calibration operating only on sparse stereo correspondences on a per-frame basis. We obtain the 5 degree of freedom extrinsic pose for each frame, with a fixed baseline, making it possible...
Body slip angle is one of the most important information for vehicle motion control; as specific sensors for body slip angle measurement are expensive, it is necessary to investigate estimation methods using existing popular sensors such as gyro sensor, encoder, camera, etc. For EV (electric vehicle), in particular, the motor response is several milliseconds which enables high performance control...
In this paper an uncooled infrared camera with embedded target detection and tracking capability is presented. The camera is built upon four main electronic cards. Sensor card is designed to read and digitize the analog output signal generated by the infrared (IR) imaging sensor. FPGA card carries out the control process of the data transfer between sensor card and other peripherals. Target detection/tracking...
It is well known in a Bayesian filtering framework, the use of inertial sensors such as accelerometers and gyroscopes improves 3D tracking performance compared to using camera measurements only. The performance improvement is more evident when the camera undergoes a high degree of motion. However, it is not well known whether the inertial sensors should be used as control inputs or as measurements...
Ego-motion estimation based on images from a stereo camera has become a common function for autonomous mobile systems and is gaining increasing importance in the automotive sector. Unlike general robotic platforms, vehicles have a suspension adding degrees of freedom and thus complexity to their dynamics model. Some parameters of the model, such as the vehicle mass, are non-static as they depend on...
Progress in LiDAR scanning has led to the availability of large scale LiDAR datasets for urban areas. We use such pre-acquired data to determine the poses of 2D monocular cameras highly accurately in real-time. This is achieved by first correctly aligning key-frames of the multi-modal data using a combination of feature and intensity-based 2D/3D registration methods. The online pose is then determined...
In this paper we present an adaptive spatio-temporal filter that aims to improve low-cost depth camera accuracy and stability over time. The proposed system is composed by three blocks that are used to build a reliable depth map of static scenes. An adaptive joint-bilateral filter is used to obtain consistent depth maps by jointly considering depth and video information and by adapting its parameters...
This paper is motivated by problems from biology involving estimation of concentration fields in a tissue sample using point measurements given by optical contactless biosensors. Due to biological constraints, the sensors may only be sparsely distributed and intermittently monitored. This paper proposes a nonbiological experimental platform, based on hydrogel and dye diffusion, for studying the problem...
Distributed analysis of video captured by a large network of cameras has received significant attention lately. Tracking moving targets is one of the most fundamental tasks in this regard and the well-known Kalman Consensus Filter (KCF) has been applied to this problem. However, existing solutions do not consider the specific characteristics of video sensor networks, which are necessary for robustness...
This paper presents a robust pose estimator for visual servoing system. Although various filters has been used as pose estimators, very limited research has been focused on the stability and robustness of pose estimators. UKF or EKF based pose estimator is one of most celebrated approaches in uncertain and noisy environment for nonlinear observations. However convergence of these filters is subject...
We present in this paper a fusion method of combining vision and inertial (accelerations and angular velocities) data for estimating and predicting position and orientation (pose) of a rapidly moving camera with respect to a fixed inertial frame. The basic framework of this fusion method is based on the Kalman filtering algorithm. By fusing the data, a fast, accurate and robust pose estimation is...
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