Let’s look at some recent research results that vividly show how information from many 2D images taken from many different locations can be combined to form a detailed 3D model of the world.
Search Results for: multiple views
For a camera moving through the environment we frequently wish to track particular world points from one frame to the next. We’ll do a quick introduction to the very large field of feature detection and matching using Harris corner features.
For a binary image that contains multiple blobs we must first transform it using connectivity analysis or region labeling. Then we can describe each of the blobs in the scene we first need to transform the image using connectivity analysis. Each of the blobs can then be described in terms of its area, centroid position, […]
We use MATLAB and some Toolbox functions to find corresponding points between two images using SURF features.
Vision is useful to us and to almost all forms of life on the planet, perhaps robots could do more if they could also see. Robots could mimic human stereo vision or use cameras with superhuman capability such as wide angle or panoramic views.
It is common to think about an assembly task being specified in terms of coordinates in the 3D world. An alternative approach is to consider the task in terms of the relative position of objects in one or more views of the task — visual servoing.
We consider multiple objects each with their own 3D coordinate frame. Now we can describe the relationships between the frames and find a vector describing a point with respect to any of these frames. We extend our previous 2D algebraic notation to 3D and look again at pose graphs.
We consider multiple objects each with its own coordinate frame. Now we can describe the relationships between the frames and find a vector describing a point with respect to any of these frames. We extend our algebraic notation to ease the manipulation of relative poses. Try your hand at some online MATLAB problems. You’ll need […]
We resume our analysis of the 6-link robot Jacobian and focus on the rotational velocity part.
We revisit the simple 2-link planar robot and determine the inverse kinematic function using simple geometry and trigonometry.