作者:
Feng XueZengwei JiangVCC Division
School of Computer and Information The International Conference on Multimedia Technology Hefei University of Technology Hefei China
MeanShift algorithm is a popular method for searching for local extreme value in the density distribution of a set of data. Traditional MeanShift object tracking algorithm mainly uses a single histogram to describe th...
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ISBN:
(纸本)9781612847719
MeanShift algorithm is a popular method for searching for local extreme value in the density distribution of a set of data. Traditional MeanShift object tracking algorithm mainly uses a single histogram to describe the color characteristics of an object, and the detection precision and stability are not good enough in a complex background due to its lacking of spatial information of pixel colors. As for this defect, this paper presents a new method combined with distribution information of space to reduce the effect of image flaws by setting a weight to pixels, on the basis of the distance from the center point of target to the current point. The experiment results show that our method promotes the tracking accuracy of moving object under a complicated environment and has better stability.
Image processing in digital computer systems usually considers the visual information as a sequence of frames. These frames are from cameras that capture reality for a short period of time. They are renewed and transm...
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ISBN:
(纸本)9789898425720
Image processing in digital computer systems usually considers the visual information as a sequence of frames. These frames are from cameras that capture reality for a short period of time. They are renewed and transmitted at a rate of 25-30 fps (typical real-time scenario). Digital video processing has to process each frame in order to obtain a filter result or detect a feature on the input. In stereo vision, existing algorithms use frames from two digital cameras and process them pixel by pixel until it is found a pattern match in a section of both stereo frames. Spike-based processing is a relatively new approach that implements the processing by manipulating spikes one by one at the time they are transmitted, like a human brain. The mammal nervous system is able to solve much more complex problems, such as visual recognition by manipulating neuron's spikes. The spike-based philosophy for visual information processing based on the neuro-inspired Address-Event-Representation (AER) is achieving nowadays very high performances. In this work we study the existing digital stereo matching algorithms and how do they work. After that, we propose an AER stereo matching algorithm using some of the principles shown in digital stereo methods.
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