A Logical Operator Oriented Face Retrieval Approach: How to Identify a Suspect Using Partial Photo Information from Different Persons?
preprintposted on 20.05.2020, 21:31 by Yiu-ming CheungYiu-ming Cheung, Zhikai Hu
Facial sketch recognition is one of the most commonly used method to identify a suspect when only witnesses are available, which, however, usually leads to four gaps, i.e. memory gap, communication gap, description-sketch gap, and sketch-image gap. These gaps limit its application in practice to some extent. To circumvent these gaps, this paper therefore focus on the problem: how to identify a suspect using partial photo information from different persons. Accordingly, we propose a new Logical Operation Oriented Face Retrieval (LOOFR) approach provided that partial information extracted from several different persons' photos is available. The LOOFR defines the new AND and OR operators on these partial information. For example, " eyes of person A AND mouth of person B" means retrieving the target person whose eyes and mouth are similar to that of person A and person B respectively, while "eyes of person A OR eyes of person B" means retrieving target person whose eyes are similar to both person A and B. Evidently, these logical operators cannot be directly implemented by INTERSECTION and UNION in set operations. Meanwhile, they are better for human understanding than set operators. Subsequently, we propose a two-stage LOOFR approach, in which the representations of partial information are learned in the first stage while the logical operations are processed in the second stage. As a result, the target photo of a suspect can be retrieved. Experiments show its promising results.