Chris
Summary:
The paper presents a tensor-based descriptor for large scale image retrieval based on sketched feature lines. The descriptor is used to search an image in the database, which is similar to the input sketch. It solves the problem of asymmetry between the binary sketch input and the full color image.
The proposed tensor descriptor provides the information about the main orientation of the gradients in a cell. The descriptor is tested by a set of 1.5 million pictures related to outdoor sceneries. It performs comparably or slightly better than the MPEG-7 edge histogram descriptor variant. And it is easy to implement and efficient in evaluation.
Discussion:
It is a good idea to search an image from a database by an input sketch. Sketch based image retrieval is also another direction in the field of sketch. The descriptor proposed in the paper is simple to implement and better than another descriptor. However, there is no extra comparison between tensor and others, so I have no idea about the performance of the descriptor. And in the experiments, an input sketch can always find a lot of candidate pictures, some of which seems unrelated to the input. So there should be other descriptors to be added to make an efficient retrieval. Also, the descriptor has some limitation in transformation, which need improvement in future.
Interesting idea, real hard part to how to thinkg of this idea.
回复删除Some Professors that I know are trying to do a search engine to search images by only text imforamtion. They must be very interesed in this paper.