I have previously introduced a feature commonly used in machine vision: LBP
LBP can effectively deal with illumination changes and is widely used in texture analysis and texture recognition.
However, LBP can only process a single 2D image. For video or image sequences, how to use LBP to extract features and capture the motion information of the video sequence. Today we introduce a feature called LBP-TOP, which was proposed by Guoying Zhao and others at the University of Oulu in Finland. It was originally used to deal with the recognition of dynamic textures, but it has now been widely used in video-based faces. Expression recognition above.
LBP-TOP is the extension of LBP from two-dimensional space to three-dimensional space. The full name of LBP-TOP is: local binary patterns from three orthogonal planes, where three orthogonal planes refers to three orthogonal planes, we know that single-frame The image has only X and Y directions, and a video or image sequence has a direction along the time axis T in addition to the X and Y directions, and the three directions XY, XT and YT are orthogonal to each other. Can look at the following picture:
Image from reference [1]
A sequence of images giving texture maps of three orthogonal planes, XY is the image we normally see, XT is the texture that each line scans along the time axis, and YT is the scan of each column along the time axis. Image, in simple terms, we can extract the LBP features in all three planes, and then connect the LBP features of the three planes, which is LBP-TOP. As shown below:
Image from reference [1]
Therefore, LBP-TOP is an extension of LBP from 2D to 3D. Compared with LBP, LBP-TOP not only considers the texture information of XY plane, but also considers the texture information of XT and YT, and the texture information of XT and YT. Record important dynamic textures.
From the LBP introduced earlier, we know that extracting LBP features, using uniform code encoding, will generate a 59-dimensional array, recording the histogram information of LBP, then the LBP-TOP feature extracts LBP in three orthogonal planes. Eventually an array of 59&TImes;3 is generated, and the dimension of the feature is increased by a factor of three. Many times, we will divide the image into blocks, and divide an image into 4&TImes; 4 blocks. Each block will generate an array of 59&TImes;3. The resulting feature has a dimension of 4&TImes; 4×59×3=2832, so LBP-TOP is a high dimensional feature.
The LBP-TOP source code can be downloaded from the official website of the University of Oulu.
Disclaimer: The pictures used on the blog are all from the reference [1]. They can only be used for learning communication. It is strictly forbidden for any commercial purpose. If you need to reprint or quote, please indicate the literature [1] as the source.
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