Skip to main content

Modeling object and action in an image

Given an object recognition system, I obtain the confident values of whether or not an object appears in an image.

I want to find out whether or not an action is likely to happen given such objects' appearance probability. I can model such a system using conditional probability, e.g., the probability of action A given the appearance of object O1, and without the appearance of object O2, etc.

Could Topic models or any LDA-style model help in this case?

Comments

Popular posts from this blog

Quick text files merging, data preparation

It's very often that in natural language processing, you will have to re-format your data to take as inputs to different systems. In this case, these simple linux commands will help you do it much quicker without having to write a script. 1. Merging two files to one file with two column Input f1 looks like this: 1 2 3 4 Input f2 looks like this: a b c d Output f3 will look like this: 1  a 2  b 3  c 4  d Command: paste f1 f2 > f3  The delimiter by default is a tab. You can also define it (for example, separated by a comma) as follows: paste -d ',' f1 f2 > f3 2.  Create a line number to each line of a text file Assume that you want to create an index to each line in a text file, i.e. inserting a line number and then a tab before the content of each line: Input f1: a b c d Output f2: 1  a 2  b 3  c 4  d Command: nl f1 > f2 3. Joining two files with a common field Input f1: 1   aaa...

Random variables

A random variable is a mapping from a sample space to real numbers $\Omega \rightarrow \mathrm{R}$ At a certain point in most probability courses, we don't see the sample space, but it's always there, lurking in the background. For example: Let $\Omega = \{(x,y); x^2 + y^2 \leq 1\}$ be the unit disc. Consider drawing a point "at random" from $\Omega$. Outcome: $\omega = (x,y)$. Examples of random variables: $X(\omega) = x$, $X(\omega) = y$, $Z(\omega) = x + y$