任何人都可以为CBIR提出好的算法？ [英] Can anyone suggest good algorithms for CBIR?

问题描述

项目：基于内容的图片检索 - 半监督（手动标记在图片上进行训练）

说明

$ b b

我在数据库中有1000000张图片。培训是手动（监督） - 为每个图像提供标题和标签。
例如：
coke.jpg
标题：Coke
标签：Coke，Can

使用图像和标签，我必须训练系统。训练后，当我给出一个新的图像（已经在数据库/全新的），系统应该输出图像可能属于的可能的标签，并显示属于每个标签的几个图像。

问题：

1）什么是图像指纹的意思？预期的图像指纹大小是多少？ （重要，因为将有数百万的图像要插入数据库中）

2）指纹在数据库中的字段格式是什么？ （重要的是因为需要快速搜索...脚本应该在不到1秒的时间内搜索1M图像数据库）

3）我们使用的描述符

提前感谢

解决方案

1. 图像指纹是SIFT描述符的集合
   



2. 建立数据库的倒排索引，允许通过量化描述符查找图像（您可以使用任何全文搜索引擎\ DB）




3. 给定图片，查找共享大量常用描述符的图片

   >
   

4. 对于那些潜在的候选人，您应该验证描述符的空间排列是否足够类似

有些文章可让您开始：

Philbin，James，et al。 Object retrieval with large vocabularies and
fast spatial matching。 Computer Vision and Pattern Recognition，2007.
CVPR'07。 IEEE会议。 IEEE，2007.

Philbin，James，et al。 Lost in quantization：Improving particular
object retrieval in large scale image databases。计算机视觉和
模式识别，2008年CVPR 2008. IEEE会议。 IEEE，
2008.

Mikulík，Andrej，et al。 学习一个精细的词汇。电脑
Vision-ECCV 2010（2010）：1-14。

Project: Content Based Image Retrieval - Semi-supervised (manual tagging is done on images while training)

Description

I have 1000000 images in the database. The training is manual (supervised) - title and tags are provided for each image. Example: coke.jpg Title : Coke Tags : Coke, Can

Using the images and tags, I have to train the system. After training, when I give a new image (already in database/ completely new) the system should output the possible tags the image may belong to and display few images belonging to each tag. The system may also say no match found.

Questions:

1) What is mean by image fingerprint? What is the image fingerprint size expected ? (important because there will be millions of images to be inserted in database)

2) What is the field format of that fingerprint in the database ? (important because a fast search is needed … script should search in a 1M images database in less than 1 second)

3) What is the descriptors (algorithms) we use to analyze them ?

Thanks in advance

解决方案

Well, this topic is very large, but here is a brief overview of a possible solution

1. Image fingerprints are collections of SIFT descriptors These are quantized both to reduce size, and to allow indexing

2. Build an inverted index of your database to allow looking up an image by quantized descriptors (you can use any full text search engine \ DB for this)

3. Given an image, lookup images which share a large amount of common descriptors

4. For those potential candidates, you should validate that the spatial arrangement of descriptors is similar enough

Some articles to get you started:

Philbin, James, et al. "Object retrieval with large vocabularies and fast spatial matching." Computer Vision and Pattern Recognition, 2007. CVPR'07. IEEE Conference on. IEEE, 2007.

Philbin, James, et al. "Lost in quantization: Improving particular object retrieval in large scale image databases." Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on. IEEE, 2008.

Mikulík, Andrej, et al. "Learning a fine vocabulary." Computer Vision–ECCV 2010 (2010): 1-14.

这篇关于任何人都可以为CBIR提出好的算法？的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！