Score Propagation Based on Similarity Shot Graph for Improving Visual Object Retrieval
Juan Manuel Barrios, José M. Saavedra · 2015
The Visual Object Retrieval problem consists in locating the occurrences of a specific entity in an image/video dataset. In this work, we focus on discovering new occurrences of an entity by propagating the detection scores of already computed candidates to other video segments. The score propagation follows the edges of a pre-computed Similarity Shot Graph (SSG). The SSG connects video segments that are similar according to some criterion. Four methods for creating the SSG are presented: two based on computing and comparing low-level visual features, one based on comparing text transcriptions, and other based on computing and comparing high-level concepts.