We develop a system for 3D object retrieval based on sketched fea- ture lines as input. For objective evaluation, we collect a large number of query sketches from human users that are related to an existing data base of objects. The sketches turn out to be gener- ally quite abstract with large local and global deviations from the original shape. Based on this observation, we decide to use a bag- of-features approach over computer generated line drawings of the objects. We develop a targeted feature transform based on Gabor fil- ters for this system. We can show objectively that this transform is better suited than other approaches from the literature developed for similar tasks. Moreover, we demonstrate how to optimize the pa- rameters of our, as well as other approaches, based on the gathered sketches. In the resulting comparison, our approach is significantly better than any other system described so far.

图像矩阵matlab代码弓检索 基于颜色直方图的BOW算法。 中文教程： 个人网站： 介绍 一种基于词袋模型的颜色直方图图像检索方法。 如何使用 只需将存储库克隆到您自己的计算机上，然后在Matlab中运行它即可。 按照顺序运行.m程序。 方法 步骤1。 提取功能 将RGB分量转换为YUV分量 为所有图像保存1536 * 64矩阵 第2步。 选择功能 将图片分成几个8 * 8的块，并将每个8 * 8的块平铺为1 * 64的向量 选择一个比率，然后选择一些1 * 64向量进行聚类。 第三步。 簇 使用Kmeans对要素进行聚类。 第四步。 分类 将原始功能划分为特定的类。 生成每个图像的频率直方图。 第五步。 计算距离 计算每两个图像之间的距离。 对距离矩阵进行排序。 步骤6。 取回 使用图像进行测试。 计算Presicion-Recall值。 如何贡献 分叉存储库 创建分支 提交您的代码 创建请求请求