Visual Constructed Representation for Object Recognition and Detection.
Visual Constructed Representation for Object Recognition and Detection.
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用于对象识别和检测的视觉构造表示。
DOI：
10.1007/978-3-642-24965-5_69
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Y. D. Sato & Y. Kuriya
中科院分区：
文献类型：
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作者：
小野渉;岡本卓;小圷成一;平田廣則;Katsumi Tateno,Yoshitaka Ohtubo;Y. D. Sato & Y. Kuriya
我们提出了一个神经启发模型的并行视觉过程的识别和检测。该模型基于Gabor特征显式表示构造。通过低通滤波器将输入图像分解为不同尺度的特征。然而，再次回收和重叠尺度特征，可以在输入图像上检测存储在存储器中的最可能的对象。这是通过尺度特征对应发现来完成的。同时，存储在存储器中的Gabor特征表示也通过选择与输入最相似的尺度特征来构造。我们还测试了我们的模型的识别能力，使用一些不同的人的面部图像。失真不变识别也证明。
We propose a neurally inspired model for parallel visual process for recognition and detection. This model is based on the Gabor feature explicit representation construction. An input image is decomposed of different scale features through the low-pass filter. Nevertheless, recycling and overlapping again the scale features, the most likely object stored in memory can be detected on the input image. This is done by scale feature correspondence finding. Simultaneously, Gabor feature representations stored in memory are also constructed by selecting the most similar scale features to the input. We also test a recognition ability of our model, using a number of facial images of different persons. Distortion invariant recognition is also demonstrated.