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This paper consists of two main contributions. First, a generic object recognition algorithm based on affinely invariant regions is proposed. Next, this algorithm is used in an Integrated Supervisory Control System (ISCS), with special attention to the human machine interaction. Experiments on an industrial robotic system are included, performing s...
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Citations
... The system under study is developed by T. Tuytelaars, A. Zaatri, Luc Van Gool and H. Van Brussel in which a generic algorithm based on local, affinely invariant regions is introduced for bringing in automation in object recognition [3]. The entire methodology is clearly depicted in Figure 2. ...
... The system under study is developed by T. Tuytelaars, A. Zaatri, Luc Van Gool and H. Van Brussel in which a generic algorithm based on local, affinely invariant regions is introduced for bringing in automation in object recognition [3]. The entire methodology is clearly depicted inFigure 2. ...
Digital Image Analysis is one of the most challenging and important tasks in many scientific and engineering applications. The two vital subtasks in image analysis are recognition and extraction of object(s) of interest (OOI) from an image. When these tasks are manually performed, it calls for human experts, making them more time consuming, more expensive and highly constrained. These negative factors led to the development of various computer systems performing an automatic recognition and extraction of visual information to bring consistency, efficiency and accuracy in image analysis. This paper focuses on the study of various existing automated approaches for recognition and extraction of OOI from an image in various scientific and engineering applications. In this study, a categorization is made based on the four principle factors (Input, Object, Feature, Attention) with which each approach is driven. All the approaches discussed in this paper are proved to work efficiently in real environment.
The Distributed Component management technique is a key technology to achieve millions monitor-points and determine the performance of the integrated supervisory control system (ISCS) in rail transit. A feasible technique applied to ISCS is described, which includes the distributed component architecture, component index with positioning and redundant components management. The application results show that the performance of ISCS is unaffected significantly by the number of nodes increased based on this technique. Therefore, this technique meets the millions monitor-points level monitoring performance requirements.
This paper describes a novel method for automatic shot cut detection, based on local region descriptors. We define a new similarity measure for temporally adjacent frames and demonstrate the advantages with accurate shot cut detection. Compared to previous approaches the proposed method is highly robust to camera and object motions and can withstand severe illumination changes and spatial editing. We apply the proposed method to different kinds of video sequences and demonstrate superior performance compared to existing methods.
In this paper, we focus on the use of Kalman filter approach to lane extraction and following. We assume a structured environment where a mobile vehicle equipped with a camera sensor, situated at a fixed distance from the vehicle frame, is navigating. A quadratic model of the road is considered. This enables the state vector of the filter to be coincided with the three parameters pertaining to a second-order polynom. The determination of the state model is carried out considering either a pure translation of the (i+1)th frame with respect to the ith frame attached respectively to the images at time t
i
and t
i+1, or a combination of both translation and rotation. While the measurement model comes down to the camera images obtained using the inverse perspective transformation, which due to the road model, permits a straightforward link between the x–y co-ordinates of images and the state vector parameters of the road. The performance of these two state models are compared with a purely measurement approach where least squares methodology is performed regardless the state model.The estimates of the filter are used by the vehicle in order to update its own knowledge about the environment and to accomplish the task of road following.Furthermore, this permits the vision system to encompass into a more general structure of Integrated Supervisory Control Systems (ISCS), where multiple functionalities are allowed.
This document, presents the AVISO system developed to provide severely disabled people (quadriplegic) with a function allowing them to grasp objects in their environment. The proposed solution relies on a dedicated robot arm with a gripper and a controller allowing automatic vision control of robot's motion. The grasping function proposed does not need marks on the objects of the environment and does not use any model of the objects. It is therefore easy to use, polyvalent and can be applied to a wide variety of objects. The AVISO system includes an intuitive man machine interface specially designed to take into account needs and interaction constraints of physically disabled people. The AVISO system was developed together with medical teams. It was tested and evaluated with disabled people of different aetiology and several valid persons under the control of occupational therapists of different hospitals and rehabilitation centres. The results are positive enough to enable to think to an industrial transfer of this technology at mid term. The paper terminates on a description of the future works, to enhance the system developed and improve our man machine interface in order to be furthermore usable by non-computer or robot specialists.
