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Selective visual attention computation model based on pulse cosine transform

A technology of cosine transformation and visual attention, applied in computing, complex mathematical operations, image data processing and other directions, can solve the problem of lack of biological rationality of computing structure, and achieve the effect of fast computing speed, simple structure and low computing complexity.

Inactive Publication Date: 2009-11-25
FUDAN UNIV
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Problems solved by technology

Because complex number calculations are impossible in the human brain, the computational structure of such methods lacks biological plausibility

Method used

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  • Selective visual attention computation model based on pulse cosine transform
  • Selective visual attention computation model based on pulse cosine transform
  • Selective visual attention computation model based on pulse cosine transform

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Embodiment Construction

[0046] 1. Experiment description

[0047] In order to objectively evaluate the performance of the PCT method of the present invention, we use two experiments to compare the PCT method, the PQFT method of literature [6] and the Saliency Toolbox (STB) method [4]. In all experiments, the saliency map resolution for PCT and PQFT methods is set to be 64 pixels wide, and the long sides are scaled accordingly. The STB saliency map resolution is automatically adjusted by its program, using the default parameter settings. Experiments of the present invention all run under Matlab 7.0 environment, and computer configuration Intel 1.50G processor, 1G memory.

[0048] 2. Natural image test

[0049] In order to evaluate the consistency between the visual attention calculation model and human visual attention, this experiment uses 120 city scene photos and 20 test people's gaze point data provided by literature [9] as a comparison benchmark. The resolution of each image in the database is...

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Abstract

The invention relates to a selective visual attention computation model based on pulse cosine transform. The model gives a input image M, whose saliency map computation steps are as follows: the formula (1) P=sign (C(M)), the formula (2) F=abs(C(P)), formula (2) SM=G*F, C and C respectively represent discrete cosine transform and inverse transform thereof, sign(.) is a sign function, and abs(.) is an absolute value function, G is a two-dimension gauss low-pass filter, wherein, only the DCT coefficient sign is reserved in formula (1), and the amplitude information is discarded; the dual factor (that is -1 and 1) simulates electric discharge of human brain neurons or not; the formula (1) is called pulse cosine transform (PCT), and the method is a called computation saliency map model, at last, the saliency map is obtained by computing formula (1) and formula (2). This method model has the advantages of simple structure, low operand, extensive application prospects in the fields of robot navigation, virtual human system, automatic focusing system and other computer visions.

Description

technical field [0001] The invention belongs to the technical field of image and video processing, in particular to a selective visual attention calculation model based on impulse cosine transform. Using this model to simulate the generation mechanism of human brain's selective visual attention, an effective visual saliency map can be generated, and the corresponding visual saliency map can be quickly calculated in space and time, so that the spatial saliency in the visual scene can be detected and motion salience. It has broad application prospects in the field of computer vision such as robot navigation, virtual human system, and auto-focus system. technical background [0002] There is a saliency-based bottom-up visual attention mechanism in the human visual system, which enables the human eye to quickly notice salient objects in complex scenes. Selective Visual Attention is a key link in information processing in the visual pathway of the human brain, which only allows...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T7/40G06T7/20G06F17/14
Inventor 余映王斌张立明
Owner FUDAN UNIV
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