First, we partition a query image
into multiple Star Student Project overlapped rectangles as
shown Star Student Project, so that local feature extraction
is completed over multiple servers. Star Student Project
Second, we quantize the extracted local features from a query image
into Star Student Project visual words using the duplicate
vocabulary in each server respectively Star Student
Projectwithout inverted indexing . Third, we tackle the issues of
both Star Student Project from a machine learning perspective,
minimizing the overall search Star Student Project latency as
well as the computational cost in traversing the Star Student
Project inverted indexing files in each server.