1. Lecture 12 What happens if we solve object recognition? 6.870 Object Recognition and Scene Understanding http://people.csail.mit.edu/torralba/courses/6.870/6.870.recognition.htm

3. Polygons world Blocks world Imagine that object recognition and segmentation is solved, so, now what?

4. Here word recognition is solved, we can access the meaning of the words. But yet, we are far from having solved language understanding. Detecting objects is just one small piece of understanding scenes (it might not even be the hardest). Images and sequence tell stories, and the structure of those stories are as complex as sentences, paragraphs and books . “ I went to the airport by car, but it took me a very long time because of the traffic.”

5. Images, with our current set of features, look more like strange sentences: I performed the action of going from one place to another in order to reach the point from where there are devices with wings in which people can get inside and perform the action of going from one place to another even when the other place is really far away. To perform the first action, I used another device that lacks wings and that, instead, has four round things attached to the sides. It took me a long time to complete the first action as there was many other people using the same device-with-four-round-things attached to them performing similar actions to me and trying to occupy the same space as me.

11. Next week Alec Rivers Scene Understanding Based on Object Relationships Gokberk Cinbis Category Level 3D Object Detection Using View-Invariant Representations Hueihan Jhuang and Sharat Chikkerur Video shot boundary detection using GIST representation Jenny Yuen Semiautomatic alignment of text and images Nathaniel R Twarog A Filtering Approach to Image Segmentation: Perceptual Grouping in Feature Space Nicolas Pinto Evaluating dense feature descriptor and multi-kernel learning for face detection/recognition Tilke Judd and Vladimir Bychkovsky Identify the same people in different photographs from the same event Tom Kollar Context-based object priors for scene understanding Tom Ouyang Hand-Drawn Sketch Recognition, A Vision-Based Approach Papers due this Friday: send PDF by email