cortex: thesis/cortex.org comparison

comparison thesis/cortex.org @ 446:3e91585b2a1c

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author	Robert McIntyre <rlm@mit.edu>
date	Tue, 25 Mar 2014 03:24:28 -0400
parents	47cfbe84f00e
children	284316604be0

comparison

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-:47cfbe84f00e
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 to interpret the actions of a simple, worm-like creature.
 #+caption: The worm performs many actions during free play such as
 #+caption: curling, wiggling, and resting.
 #+name: worm-intro
-#+ATTR_LaTeX: :width 13cm
+#+ATTR_LaTeX: :width 15cm
 [[./images/worm-intro-white.png]]
+#+caption: The actions of a worm in a video can be recognized by
+#+caption: proprioceptive data and sentory predicates by filling
+#+caption:  in the missing sensory detail with previous experience.
+#+name: worm-recognition-intro
+#+ATTR_LaTeX: :width 15cm
+[[./images/worm-poses.png]]
+One powerful advantage of empathic problem solving is that it
+factors the action recognition problem into two easier problems. To
+use empathy, you need an /aligner/, which takes the video and a
+model of your body, and aligns the model with the video. Then, you
+need a /recognizer/, which uses the aligned model to interpret the
+action. The power in this method lies in the fact that you describe
+all actions form a body-centered, rich viewpoint. This way, if you
+teach the system what ``running'' is, and you have a good enough
+aligner, the system will from then on be able to recognize running
+from any point of view, even strange points of view like above or
+underneath the runner. This is in contrast to action recognition
+schemes that try to identify actions using a non-embodied approach
+such as TODO:REFERENCE. If these systems learn about running as viewed
+from the side, they will not automatically be able to recognize
+running from any other viewpoint.
+Another powerful advantage is that using the language of multiple
+body-centered rich senses to describe body-centerd actions offers a
+massive boost in descriptive capability. Consider how difficult it
+would be to compose a set of HOG filters to describe the action of
+a simple worm-creature "curling" so that its head touches its tail,
+and then behold the simplicity of describing thus action in a
+language designed for the task (listing \ref{grand-circle-intro}):
 #+caption: Body-centerd actions are best expressed in a body-centered
 #+caption: language. This code detects when the worm has curled into a
 #+caption: full circle. Imagine how you would replicate this functionality
 #+caption: using low-level pixel features such as HOG filters!
 (and (< 0.55 (contact worm-segment-bottom-tip tail-touch))
 (< 0.55 (contact worm-segment-top-tip    head-touch))))))
 #+end_src
 #+end_listing
-#+caption: The actions of a worm in a video can be recognized by
-#+caption: proprioceptive data and sentory predicates by filling
-#+caption:  in the missing sensory detail with previous experience.
-#+name: worm-recognition-intro
-#+ATTR_LaTeX: :width 10cm
-[[./images/worm-poses.png]]
-One powerful advantage of empathic problem solving is that it
-factors the action recognition problem into two easier problems. To
-use empathy, you need an /aligner/, which takes the video and a
-model of your body, and aligns the model with the video. Then, you
-need a /recognizer/, which uses the aligned model to interpret the
-action. The power in this method lies in the fact that you describe
-all actions form a body-centered, rich viewpoint. This way, if you
-teach the system what ``running'' is, and you have a good enough
-aligner, the system will from then on be able to recognize running
-from any point of view, even strange points of view like above or
-underneath the runner. This is in contrast to action recognition
-schemes that try to identify actions using a non-embodied approach
-such as TODO:REFERENCE. If these systems learn about running as viewed
-from the side, they will not automatically be able to recognize
-running from any other viewpoint.
-Another powerful advantage is that using the language of multiple
-body-centered rich senses to describe body-centerd actions offers a
-massive boost in descriptive capability. Consider how difficult it
-would be to compose a set of HOG filters to describe the action of
-a simple worm-creature "curling" so that its head touches its tail,
-and then behold the simplicity of describing thus action in a
-language designed for the task (listing \ref{grand-circle-intro}):
 ** =CORTEX= is a toolkit for building sensate creatures
 Hand integration demo

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comparison thesis/cortex.org @ 446:3e91585b2a1c