Google's Latest Machine Vision Breakthrough 113
mikejuk writes "Google Research recently released details of a Machine Vision technique which might bring high power visual recognition to simple desktops and even mobile computers. It claims to be able to recognize 100,000 different types of object within a photo in a few minutes — and there isn't a deep neural network mentioned. It is another example of the direct 'engineering' approach to implementing AI catching up with the biologically inspired techniques. This particular advance is based on converting the usual mask-based filters to a simpler ordinal computation and using hashing to avoid having to do the computation most of the time. The result of the change to the basic algorithm is a speed-up of around 20,000 times, which is astounding. The method was tested on 100,000 object detectors using over a million filters on multiple resolution scalings of the target image, which were all computed in less than 20 seconds using nothing but a single, multi-core machine with 20GB of RAM."
Re:Coming to mobile? (Score:5, Informative)
Wait, your phone can decode video?!? In real time, playing the movies at normal speed? How many kilograms does it weigh, and how long is the power lead? How big is the mortgage on it? (/socraticmethod)
The computer innovation process broadly goes like this: first algorithm sort-of works but is incredibly inefficient - tweaks on this - a rethinking of the whole approach that leads to massive speed-ups - further refinement - implementation of the algorithm in hardware, where it becomes just another specialized processor - everybody profits!.
This article is about the third, or possibly fourth, phase of the process. If it it works out, phase 5 is straightforward. By itself, step 5 typically leads to two orders of magnitude increase in performance, three orders of magnitude decrease in power consumption, and two to four orders of magnitude decrease in cost.
Phases 6 and 7 happen if and when enough people find the provided service useful. (If technologies are no good, that's when only rich people have them. Successful technologies, everyone gets access to eventually.)
Re:Spatial Hashing (Score:5, Informative)
Yes, it's a breakthrough. It won the best paper award at this year's Conference on Computer Vision and Pattern Recognition, a tier 1 computer vision conference.
Hashing invarient properties in images isn't new, but,
banded winner-take-all hashing of histograms-of-oriented-gradient part filters and then using matches across those bands to identify a test feature's nearest neighbors, while simultaneously computing an upper bound or exact dot products of those test features with their nearest learned features, for up to 100,000 objects with small amounts of memory, is new.
Re:Can it find Waldo?... (Score:3, Informative)
There are several non-too-creepy apps that can identify plant species by a smartphone-photo of a single leaf.
http://leafsnap.com/about/
They seem to request metadata directly via your phone's location and time-of-request (their server, not your phone, does the pattern-matching). Which is convenient, although it may place you at a time and place you may rather not be placed, for instance if burying pirate gold under a particular tree.