Most robotic grasping tasks assume a stationary or fixed object. In this paper, we explore the requirements for tracking and grasping a moving object. The focus of our work is to achieve a high level of interaction between a real-time vision system capable of tracking moving objects in 3-D and a robot arm with gripper that can be used to pick up a moving object. There is an interest in explorin...

A motion trajectory tracking method using a novel visual attention model and kernel density estimation is proposed in this paper. As a crucial step, moving objects detection is based on visual attention. The visual attention model is built by combination of the static and motion feature attention map and a Karhunen-Loeve transform (KLT) distribution map. Since the visual attention analysis is c...

In moving object databases, many authors assume that number and position of objects to be processed are always known in advance. Detecting an unknown moving object and pursuing its movement, however, is usually left to tracking algorithms outside the database in which the sensor data needed is actually stored. In this paper we present a solution to the problem of efficiently detecting targets o...

Abstract   In this paper, we propose a new method for kernel based object tracking which tracks the complete non rigid object. Definition the union image blob and mapping it to a new representation which we named as potential pixels matrix are the main part of tracking algorithm. The union image blob is constructed by expanding the previous object region based on the histogram feature. The pote...

An object tracking system using a variable search window (VSW) algorithm based on color and feature points is proposed. A meanshift algorithm is an object tracking technique that works according to color probability distributions. An advantage of this algorithm based on color is that it is robust to specific color objects; however, a disadvantage is that it is sensitive to non-specific color ob...

Detection and tracking are important components of many computer vision applications including automated surveillance. Object detection should overcome challenges such as changes in object appearances, illumination, and shadows. In our system, Gaussian mixture models are used for background subtraction to detect moving objects. Tracking is challenging because measurements from the object detect...

Using a depth camera, the KinectFusion algorithm permits tracking the camera poses and building a dense 3D reconstruction of the environment simultaneously in real-time. We present an extension to this algorithm that allows additionally the concurrent tracking and reconstruction of several moving objects within the perceived environment. This is achieved through an expansion of the GPU processi...

In this paper, we develop a heuristic algorithm to construct an efficient object tracking in wireless sensor networks (WSNs). Such wireless sensor network has to be designed to achieve efficient object tracking for given arbitrary topology of wireless sensor networks. We consider the two-way object moving frequency of each pair of sensor nodes and link transmission cost. This problem is formula...

Research in motion analysis has evolved over the years as a challenging field, such as traffic monitoring, military, medicine and biological sciences etc. Detection and tracking of moving objects in video sequences can offer significant benefits to motion analysis. In this an approach is proposed for the detection and tracking of moving object in an image sequence. Two consecutive frames from i...

In order to satisfy the moving object diction and tracking’s real-time and self-learning performance, the method which combines background substraction and threshold image segmentation on HSV space is presented in this paper. Detecting the real-time image and getting the threshold of HS space. Next, the moving object’s area is got by the thresholds segment. Third, getting the center and realize...