Benchmark for anonymous video analytics
Abstract Out-of-home audience measurement aims to count and characterize the people exposed to advertising content in the physical world. While audience measurement solutions based on computer vision are of increasing interest, no commonly accepted benchmark exists to evaluate and compare their perf...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2021-10-01
|
| Series: | EURASIP Journal on Image and Video Processing |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s13640-021-00571-5 |
| _version_ | 1829496450733572096 |
|---|---|
| author | Ricardo Sanchez-Matilla Andrea Cavallaro |
| author_facet | Ricardo Sanchez-Matilla Andrea Cavallaro |
| author_sort | Ricardo Sanchez-Matilla |
| collection | DOAJ |
| description | Abstract Out-of-home audience measurement aims to count and characterize the people exposed to advertising content in the physical world. While audience measurement solutions based on computer vision are of increasing interest, no commonly accepted benchmark exists to evaluate and compare their performance. In this paper, we propose the first benchmark for digital out-of-home audience measurement that evaluates the vision-based tasks of audience localization and counting, and audience demographics. The benchmark is composed of a novel, dataset captured at multiple locations and a set of performance measures. Using the benchmark, we present an in-depth comparison of eight open-source algorithms on four hardware platforms with GPU and CPU-optimized inferences and of two commercial off-the-shelf solutions for localization, count, age, and gender estimation. This benchmark and related open-source codes are available at http://ava.eecs.qmul.ac.uk . |
| first_indexed | 2024-12-16T07:31:39Z |
| format | Article |
| id | doaj.art-3e7a695f13994b4eb190d63358fed1ad |
| institution | Directory Open Access Journal |
| issn | 1687-5281 |
| language | English |
| last_indexed | 2024-12-16T07:31:39Z |
| publishDate | 2021-10-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Image and Video Processing |
| spelling | doaj.art-3e7a695f13994b4eb190d63358fed1ad2022-12-21T22:39:20ZengSpringerOpenEURASIP Journal on Image and Video Processing1687-52812021-10-012021112710.1186/s13640-021-00571-5Benchmark for anonymous video analyticsRicardo Sanchez-Matilla0Andrea Cavallaro1Centre for Intelligent Sensing, Queen Mary University of LondonCentre for Intelligent Sensing, Queen Mary University of LondonAbstract Out-of-home audience measurement aims to count and characterize the people exposed to advertising content in the physical world. While audience measurement solutions based on computer vision are of increasing interest, no commonly accepted benchmark exists to evaluate and compare their performance. In this paper, we propose the first benchmark for digital out-of-home audience measurement that evaluates the vision-based tasks of audience localization and counting, and audience demographics. The benchmark is composed of a novel, dataset captured at multiple locations and a set of performance measures. Using the benchmark, we present an in-depth comparison of eight open-source algorithms on four hardware platforms with GPU and CPU-optimized inferences and of two commercial off-the-shelf solutions for localization, count, age, and gender estimation. This benchmark and related open-source codes are available at http://ava.eecs.qmul.ac.uk .https://doi.org/10.1186/s13640-021-00571-5Anonymous video analyticsBenchmarkAudience measurementPerformance evaluation |
| spellingShingle | Ricardo Sanchez-Matilla Andrea Cavallaro Benchmark for anonymous video analytics EURASIP Journal on Image and Video Processing Anonymous video analytics Benchmark Audience measurement Performance evaluation |
| title | Benchmark for anonymous video analytics |
| title_full | Benchmark for anonymous video analytics |
| title_fullStr | Benchmark for anonymous video analytics |
| title_full_unstemmed | Benchmark for anonymous video analytics |
| title_short | Benchmark for anonymous video analytics |
| title_sort | benchmark for anonymous video analytics |
| topic | Anonymous video analytics Benchmark Audience measurement Performance evaluation |
| url | https://doi.org/10.1186/s13640-021-00571-5 |
| work_keys_str_mv | AT ricardosanchezmatilla benchmarkforanonymousvideoanalytics AT andreacavallaro benchmarkforanonymousvideoanalytics |