Hypercolumn-array based image representation and its application to shape-based object detection

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• 作者：Hui Wei^a ; ^{weihui@fudan.edu.cn} ; Zheng Dong^a ; Bing Liu^a ; ^b
• 关键词：Orientation column ; Shape representation ; Object recognition ; Primary visual cortex
• 刊名：Applied Soft Computing
• 出版年：2017
• 出版时间：March 2017
• 年：2017
• 卷：52
• 期：Complete
• 页码：333-347
• 全文大小：5370 K
• 卷排序：52

文摘

We simulate the mechanism of hypercolumns in the V1 cortex of mammals that selectively responds to bar stimuli, and design an orderly-arranged array to extract and represent edges in an image. Based on the neighborhood of units in the array, we construct a graph whose node represents a short line segment of a contour. We search along the routes in that graph and compare them with a shape template for object detection. Organizing segments of contour into a graph greatly upgrades the level of image representation, remarkably reduces the load of combinations, significantly improves the efficiency of object searching, and facilitates the intervening of high-level knowledge.