[nl]

And yet facial-recognition is now freely available to consumers (Picasa, Facebook etc), our phones have blink detection, 3D motion detection and tracking is available to consumers for ~$100 (Kinect).

I'm not familiar with the PASCAL object detection challenge, but I just had a quick look. It's hard - if I understand it correctly, classifiers had to categorize photos into containing 5 types of objects form the 1000 leaf nodes of http://www.image-net.org/challenges/LSVRC/2010/browse-synset.... (Based on the description from http://www.image-net.org/challenges/LSVRC/2010/pascal_ilsvrc...). I'm having trouble understanding the scoring scheme (how is flat cost calculated?), but based on this I'm quite impressed.

I'm human (yes, I swear it's true), and I couldn't classify things like different breeds of poodle: http://www.image-net.org/synset?wnid=n02113712

[danger]

There are many different actual tasks that technically are PASCAL challenges, but when people say "PASCAL VOC challenge" (Visual Object Classes), they typically mean either the _classification_ or _detection_ challenge:

Classification: For each of the twenty classes, predicting presence/absence of an example of that class in the test image.

Detection: Predicting the bounding box and label of each object from the twenty target classes in the test image.

Neither uses the full ImageNet data set. Instead, it's images from 20 classes of object, like shown here: http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2010/exam...

[nl]

Here are the results: http://pascallin.ecs.soton.ac.uk/challenges/VOC/voc2010/resu...

I find the results quite impressive - especially for classification - 90%+ precision for detecting people in photos seems like a good result.