1. A method, comprising: identifying a pool of features from multiple types of input, the pool of features comprising a first video feature from a video input, the first video feature comprising a parent rectangle within a feature rectangle in an image of the video input; calculating a numeric value associated with the first video feature by summing values of pixels in the parent rectangle; and generating a classifier for speaker detection using a learning algorithm wherein nodes of the classifier are selected using the pool of features, based on the numeric value associated with the first video feature.
1. A method, comprising: identifying a pool of features from multiple types of input, the pool of features comprising a first video feature from a video input, the first video feature comprising a parent rectangle within a feature rectangle in an image of the video input; calculating a numeric value associated with the first video feature by summing values of pixels in the parent rectangle; and generating a classifier for speaker detection using a learning algorithm wherein nodes of the classifier are selected using the pool of features, based on the numeric value associated with the first video feature. 2. The method of claim 1 , the parent rectangle comprising two or more sub-rectangles.