Occlusion is always a problem when counting vehicles in congested traffic. This paper tries to present an approach to solve the problem. The proposed approach consists of three main procedures. Firstly, a modified background subtraction is performed. The aim is to segment slow moving objects from an illumination-variant background. Secondly, object tracking is performed, where the CONDENSATION algorithm is used. This can avoid the matching problem. Thirdly, an inspecting procedure is executed. When a bus firstly occludes a car and then the bus moves away a few frames later, the car will appear in the scene. The inspecting procedure should find the “new” car and add it as a tracking object.
An algorithm of fault diagnosis is proposed for vision module on the intelligent agent. The basic theory to generate the expected area is of the fundamental matrix, which is an important concept of epipolar geometry. The proposed method can be performed in real time to judge whether the system is in good health. Compared with the conventional methods, our method doesn’t need additional sensors and requires less CPU load. Experiment shows that the method is reasonable.
A new MD (multiple description) video coding method, which is based on balanced multiwavelet image transformations, is proposed here. First, we apply balanced multiwavelet transformation to the image; then, corresponding components of each sub-band are gathered together, so that we can decompose the image into 4 MDs. By treating every frame of the video sequences like this, we can get a theme of MD video coding. A practical MD coding theme must satisfy two requirements. First, each description should carry the same amount of information. Secondly, there must be dependence between each description. Among commonly used multiwavelets, we find that only balanced multiwavelets can satisfy these two requirements. Furthermore, based on the feature of CARDBAL2 multiwavelet and strict mathematical deductions, we also find a way to estimate the lost descriptions. The experimental results presented in this paper show that, even when 75% of the data of the image are lost, we could still get a good-quality recovered image, with a PSNR value of nearly 30dB.
In this paper, a practical approach of the calibration of a stereovision system is proposed. At first, the internal parameters are calibrated with the traditional method. Then, after the two cameras are mounted, relative position of the two cameras is determined by solving the essential matrix. Thus, elaborate setup of the control points is avoided, which allows the method be applied outside laboratory environments. Additionally, a new solution of the essential matrix is described, which is easier to be comprehended and implemented. Chessboard-like patterns are used in the calibration and the grid corners are detected automatically by a new scheme based on the symmetry in the local area. Experiments have been carried out to test the approach. Results achieved by the proposed approach are as accurate as those achieved by the traditional methods.