Benchmark for Anonymous Video Analytics
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Estimating the number of people exposed to digital signage is important to help measuring the return on investment of digital out-of-home advertisement. However, while audience measurement solutions are of increasing interest, no commonly accepted benchmark exists to evaluate their performance. In this paper, we propose the first benchmark for digital out-of-home audience measurement that evaluates the tasks of audience localization and counting, and audience demographics. The benchmark is composed of a novel video dataset captured in multiple indoor and outdoor 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.
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