Proposed Guidelines for Research Publications using SVS Customer Data

1. Proposed Guidelines for Research Publications using SVS Customer Data Rick Kjeldsen SharathPankanti

2. Problem • Research team is asked to make extensive use of SVS customer data • Real customer data presents different problems than “similar” data in the public domain • Often, the most important research addresses these differences • Researchers are evaluated in part on their academic publication record • Publication requires example images • Publication requires performance results based on image data • Publication timelines do not permit an extensive review process BUT • Customer data must be kept confidential, specifically information about where security cameras are located and how to defeat them

3. Proposed guidelines • Image data will include no information which could reasonably be used to identify the location. This will include • Street and other signs or markings that could identify the location • Recognizable structures or road configurations • Long views where city-scapes may be recognizable • Performance data will be anonymous with respect to data source • Problems will be discussed in generic context and will not reveal any proprietary information. • Details (e.g. use cases) or problems specific to one customer will not be discussed, even anonymously • Specific techniques for defeating the system or avoiding detection will not be discussed. • Images where individuals are recognizable will not be used without their permission • There will be no reference to specific customers or code release versions • SVS / VCAS will not be mentioned by name • Proprietary technology must be protected before publication

4. Examples • The following are examples of image data which are sufficiently anonymous that they may appear in a publication • The following web images illustrate cameras that are not sufficiently anonymous to be used