Pattern Recognition Letters

Call for Papers

Special Issue on Video Analytics for Audience Measurement in Retail and Digital Signage


The retail and advertisement industries are becoming more pervasive, with the need of measuring engagement of viewers/shoppers with newly launched campaigns. The Digital Signage sector represents today the third advertising medium in terms of annual revenues after mobile and online advertising. The trend is exponentially increasing and brands, network aggregators and media planner’s needs are moving toward understanding level of engagement of viewers in order to measure their reaction to new products. While online advertising is mature and has established measurements tools, there are sectors of the sale industry where grabbing anonymous information from the human being is important to measure the effectiveness of a campaign and to take prompt actions to maximize the attention of people to the ad or to the product space. Point of sale and on-shelf solutions are also getting more pervasive due to the needs of measuring how shoppers engage, where attention and gaze estimation in free environment is difficult to perform. Also, measuring the customer experience will allow to stimulate a multidisciplinary approach which will bring ethologist, psycologist, marketing and media planner professionals to eventually propose new metrics, to study and understand social behaviours of social media.

Video analytics may help understanding the effectiveness of the branded message by studying and measuring public opinion and polling, geographical concentration of conversation of viewers. To this aim, computer vision and pattern recognition technologies will play an important improvement in audience measurement for its capability to understand several visual cues such as demographics, free gaze estimation, dwell time, emotion and group people proxemics, where low spatial resolution of acquired subjects, changing of the pose, occlusion, illumination changes, large variability of intra-class female age and ethnicity cohorts represent some critical aspects for recognition.

The aim of this Special Issue is to provide latest unpublished research papers on methods for audience measurements in the retail and Digital Signage sectors, attraction of end-users, and stimulate the creation of appropriate benchmark dataset to be used as a reference tool for the development of novel audience measurement algorithms. Researchers are invited to submit papers under the following topics (but not limited to):

List of topics

Research papers are solicited in, but not limited to, the following topics:

  • Dwell time estimation
  • Gender recognition
  • Age and Age group estimation
  • Behaviour analysis
  • People counting in multi-camera network
  • People recurrence in long time window
  • Clothing attributes
  • Ethnicity recognition
  • Emotion analysis
  • Free eye gaze estimation
  • Group of related people: detection, tracking and behaviour analysis
  • Modelling consumer behaviour
  • Path optimization and queue management in the point of sale
  • Annotated Dataset proposal
  • Privacy preserving in audience measurements
  • Other visual cues for customer profiling

Submissions and revisions

Submissions to the VAAM Special Issue must include new, unpublished, original research. Papers must be original and have not been published or submitted elsewhere. All papers must be written in English. The submissions will be blind reviewed by at least three reviewers. Papers should be submitted electronically using the Elsevier PRL submission system by indicating “VAAM” as article type, and following the Instructions for Authors ( All submissions will undergo initial screening by the Guest Editors to fit the theme of the Special Issue and prospects for successfully negotiating the review process.


Submission Deadline: September 15, 2015
First Notification: December 15, 2015
Revised manuscript submission: January 30, 2016
Notification of Final Decision: April 15, 2016


Lead guest editor
Cosimo Distante (, National Institute of Optics - CNR IT

Guest editors
Sebastiano Battiato (, University of Catania IT
Andrea Cavallaro (, Queen Mary University of London UK