Image Recognition Using Viola-Jones

Ellen Talbot lays out some of the basics of image recognition:

Aggregate channel features (ACF) is a variation of channel features, which extracts features directly as pixel values in extended channels without computing rectangular sums at various locations and scales.

Common channels include the colour channels, such as grey-scale and RBG, but many other channels can be encoded, depending on the difficulty of your problem (e.g. gradient magnitude and gradient histograms).

ACF has advantages, such as a richer representation, accelerated detection speed and more accurate localisation of objects in the images when used in conjunction with a boosting method.

Click through for more, including a few resources around the Viola-Jones algorithm.

Related Posts

Calculating TF-IDF Using Apache Spark

Arseniy Tashoyan shows us how to calculate Term Frequency-Inverse Document Frequency using Apache Spark: TF-IDF is used in a large variety of applications. Typical use cases include: Document search. Document tagging. Text preprocessing and feature vector engineering for Machine Learning algorithms. There is a vast number of resources on the web explaining the concept itself […]

Read More

Using The Azure Data Science VM With GPUs

Jennifer Marsman has some tips and tricks around using the Azure Data Science Virtual Machine on an instance running with GPU support: To get GPU support, you need both hardware with GPUs in a datacenter, as well as the right software – namely, a virtual machine image that includes GPU drivers so you can use […]

Read More

Categories

March 2018
MTWTFSS
« Feb Apr »
 1234
567891011
12131415161718
19202122232425
262728293031