Low-Power Image Recognition Challenge

Significant progress has been made in recent years using computer programs recognizing objects in images. Meanwhile, many cameras are embedded in battery-powered systems (such as mobile phones, wearable devices, and drones) and energy efficiency is essential. Even though many research papers have been published on the topics related to low power and image recognition, there does not exist a common metric for comparing different solutions in terms of (1) energy efficiency and (2) accuracy in recognition. Low-Power Image Recognition Challenge (LPIRC) is, to our knowledge, the only on-site competition that considers both energy consumption and recognition accuracy. LPIRC was held as one-day workshops in the Design Automation Conference in 2015 and 2016. Each participating team brought their own system to the workshops. The referee system of LPIRC includes (1) an intranet, (2) a power meter, and (3) an HTTP server that provided the images and accepted the answers from the contestants' systems. The scores were the ratio of recognition accuracy and the energy consumption. The winner of 2016 was able to analyze 7,347 images and achieve 9.44% normalized mAP (mean average precision) with average power consumption of 4.7 W. Another team analyzed 1,020 images and achieved 25.7% normalized mAP.