Implementing a multi-touch event system to deliver blob events to registered widgets (and creating a demo photo application with inertia) part 1 of 2

In my previous posts we've discussed blob extraction and tracking. Now we'll take it one step further and design an event system to handle those events and deliver them to registered widgets. In this post we will focus on the event system and the widget base class. In the next post we will extend the widget base class to create a photo application like below. I've drawn up a quick flowchart of what we'll be attempting to implement. Everything in the left column under "Input System" we've Read more [...]

C++ implementation of the Connected Component Labeling method using the Disjoint Set data structure

In the post before last we discussed using cvBlobsLib as a tool for blob extraction. We're going to revisit the extraction theme and look at a C++ implementation of the Connected Component Labeling method, but before we do that we're going to look at an implementation of the Disjoint Set data structure that will provide us with the necessary tool for generating equivalence sets. The Disjoint Set data structure allows us to track elements partitioned into disjoint subsets. Two sets are disjoint Read more [...]

Fiducial detection based on topological region adjacency information with identification by angle information

In my last post we discussed blob extraction and event tracking. We will continue with that project by adding support for two-dimensional fiducial tracking. We will attempt to implement the fiducial detection algorithm used on the Topolo Surface1. We will first describe the fiducials and how their properties are encoded in their structure, and we will add a class to our project to support fiducial detection and rendering. When finished we will obtain the following renderings: Below Read more [...]

Detecting blobs with cvBlobsLib and tracking blob events across frames

In my previous post we discussed using OpenCV to prepare images for blob detection. We will build upon that foundation by using cvBlobsLib to process our binary images for blobs. A C++ vector object will store our blobs, and the center points and axis-aligned bounding boxes will be computed for each element in this vector. We will define a class that operates on this vector to track our blobs across frames, converting them to an event type. An event will be one of three types, BLOB_DOWN, BLOB_MOVE, Read more [...]

Using OpenCV to process images for blob detection (with SDL and OpenGL for rendering)

In this post I will discuss how you can capture and process images in preparation for blob detection.  A future post will discuss the process of detecting and tracking blobs as well as fiducials, but here we are concerned with extracting clean binary images that will be passed to our detector module.  We will use OpenCV's VideoCapture class to extract images from our capture device and then pass these images through a series of filters so that we end up with a binary image like below. We Read more [...]