Google Research Leads To Automated Real-Time Pedestrian Detection

An anonymous reader writes with a link to a story about one of the unexciting but vital bits of technology that will need to be even further developed as autonomous cars' presence grows: making sure that those cars don't hit people. Google researchers have recently presented findings about a method that tops previous ones for real-time pedestrian detection using neural nets "that is both extremely fast and extremely accurate." From the article: There are other approaches that provide a real-time solution on the GPU but in doing so, have not achieved accuracy targets (in this real-time approach there was a miss rate of 42% on the Caltech pedestrian detection benchmark). Another approach called the VeryFast method can run at 100 frames per second (compared to the Google team's 15) but the miss rate is even greater. Others that emphasize accuracy, even with GPU acceleration, are up to 195 times slower.

Comments

Re:Two ideas

[Gravis Zero]

it seems that the new much-more-accurate algorithm still misses 30% of cases. For me, hurting (even killing) 3 out of 10 pedestrians still sounds quite bad.

missing 30% isn't killing 3 out of 10 people, it's killing 7 out of 10 people which is a solid 70 points or 210 points if you are drifting. #Carmageddon