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With the arrival of the aging society, more and more empty nest elderly appear. In order to solve the security problems caused by the fall of the empty nest elderly, this paper proposes a method to judge the elderly's fall based on motion tracking. The method combines LBP features and chromaticity features to detect the moving target. Then, the Kalman filter and Camshift were used to track the detected...
In recent trends the movable object detection is locating its position & location with reference of higher weighted particles. The color based target detection & tracking is the main role for developing the application like video streaming, research area like color template matching processing & open source visual surveillance area. A Bayesian filtering method & video analysis modeling...
In order to improve the docking success rate in Automated Aerial Refueling (AAR), it is important to identify the receiver aircraft's receptacle for boom receptacle refueling (BRR). Meanshift tracking algorithm only considers the H component color statistics of the target area, lacking spatial information, could easily lead to inaccurate tracking. Besides, Meanshift tracking algorithm could easily...
In order to accurately track sea cucumber on the assembly line to realize automatic grabbing using mechanical arm, an object tracking method based on Mean-shift algorithm was proposed. Firstly, the contours of the objects was extracted from the original image to select tracking target, and then the local image was cropped at the same position and local area in the second frame, and mean-shift algorithm...
Multi-targets tracking has shown great prospects in ocean investigations. In this paper, we apply the adaptive background mixture models to extracts the moving target from the image sequences, and propose a new method which is made use of the EKF and SURF-RANSAC to realize multi-targets tracking via multiple underwater cameras. In this method the centroid coordinate homographic mapping and the Speeded...
To achieve better performance of visual tracking, an improved TLD tracking algorithm was proposed. Firstly, the performance of objects detection classifiers was improved by the usage of the color attributes of objects. The accuracy of objects detector was boosted by using the color attributes of initial object, which was labeled manually. Secondly, Kalman Filter is adopted to estimate localization...
Human gait capture by vision plays an important role in the guidance for the rehabilitation of the lower limbs dysfunction patients. Unfortunately, it is not included in most of the present rehabilitation devices. This paper presents a novel real-time system for human gait capture by detecting the joints trajectory to obtain 3-D information of the joints motion by Kinect. Firstly, we put markers on...
In order to overcome a shortcoming of traditional CAMSHIFT which requires manual target designation and object color similarity between frames, this paper proposes an image tracking algorithm by a combination of CAMSHIFT with Adaboost object detection and the Kalman estimator. The proposed method alleviates loss-of-track problems caused by accelerating target motion and color noise. Robustness against...
To reduce the tracking errors caused by high-speed motion and variable motion in the process of moving target tracking, a novel Mean-Shift tracking algorithm based on Kalman filter using adaptive window and sub-blocking is proposed in this paper. Moving target's utmost position is predicted by combining Kalman filter and historical information, which is used as the initial position. During describing...
Visual-attention-model (VAM) is a kind of model with good robustness of bionic vision. For ground object sensed on UAV (Unmanned Aerial Vehicle) platform, in this paper object detection and tracking algorithm based on VAM and extended Kaiman filter (EKF) is proposed, and applied to the ground surroundings for object detection and tracking. In order to quickly extract the ground objects in aerial images,...
Tracking objects using Mean Shift algorithm fails when there is a full/partial occlusion or when the background color and the desired object are close. In this paper we proposed a method using Kalman Filter and Mean Shift for handling these situations. Using similarity measure of Mean Shift algorithm we are able to detect an occlusion. Kalman Filter comes into the play for occlusion handling in a...
In this paper we present a novel method for object tracking in surveillance scenes. We improve the 'ViBe' background subtraction algorithm by adding the scale invariant local ternary pattern operator 'SILTP' so as to detect moving shadow and increase the accuracy of segmentation. An object tracking method based on Compressive Tracking and Kalman filter by using the result of background subtraction...
In the application and prospect of computer vision technique, video target recognition and tracking was an important research subject. In this article, we present a new approach to track moving target with mean shift algorithm and kalman filter. With this approach, we do not need to calculate the Bhattacharyya coefficient, so we can track the moving target at real time. But we found that the robust...
The tracking algorithm of Camshift is only used in simple background with certain color. In this paper, an improved Camshift algorithm is proposed. Firstly the precision localization of the target is realized by wavelet which has the characteristics of multi-resolution analysis and time-frequency local window analysis, then the coordinate of center-of-mass is calculated based on the detected initial...
A new visual object tracking algorithm is proposed by using joint feature points correspondences and color similarity of the moving object to solve the background disturbance. This tracking algorithm is based on particle filtering in which a new method of computing each sample weight is proposed. Each sample weight can be obtained through measuring the similarities of color histogram and feature points...
The goal of target tracking is to find the targets between the consecutive frames in image sequences. Many tracking algorithms have been proposed and implemented to overcome difficulties that arise from noise, occlusion, clutter, and changes in the foreground objects or in the background environment. For the tracking methods based on traditional Kalman filter algorithm, there are several candidate...
Recently a data set was collected that includes video data and imaging sonar data in the underwater environment. This data set provides a unique example of a data fusion problem that is not commonly found in the underwater environment. This paper presents the fusion of data from a video camera and an imaging sonar, which is then processed by a target tracking algorithm.
The aim of this paper is to present an algorithm for multiple object tracking and video summarization in a scene filmed by one or several cameras. We propose a computationally efficient real time human tracking algorithm, which can 1) track objects inside the field of view (FOV) of a camera even in case of occlusions; 2) recognize objects that quit and then return on a camera's FOV; 3) recognize objects...
This paper describes a method for traffic signs detection, tracking and recognition. Color and shape are combined to detect signs. Hue and saturation are used to detect the red color of the sign. Circles are detected through the improved round-degree method of extracting area feature parameters. An improved Kalman filter is introduced to track multiple targets in the next frames. A feature extraction...
To track human target real-time under dynamic scene, an automatic target tracking system based on IP PTZ camera was designed and an algorithm for tracking human target based on the system was proposed. Adaptive three-frame subtraction method was used to detect moving object and Camshift combined with Kalman filter was utilized to track object automatically. As Camshift algorithm suffers from low color...
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