Tutorial Visual Perception Towards Computer Vision Steps in 3D Object Modelling Camera Modelling and Calibration StereoVision & Epipolar Geometry Fundamental Matrix Estimation Coded Structured Light

Human Vision: Identify objects Locate its 3D position. Image acquisition Image interpretation

The Human Eye ? Eye shape: Cornea: Transparent surface. Sclera: Outer cover composed of a fibrous coat that surrounds the choroid. Choroid: a layer of blood capillaries. Retina: layer inside the choroid composed of two types of receptors (rods and cones) and a netword of nerves. Optic nerve: Retinal nerves leave the eye to the brain trough the optic nerve bundle. Image enhancement: Cornea: Transparent surface. Lens: Focuses the light to the retina surface to perform proper focus of near and distant objects. Iris: Acts as a diaphragm to control the amount of light entering the eye.

How an eye is working ? Image acquisition: Retina: Composed of 100 M. Rods: Long slender receptors. Sensitive at low levels of light. 6.5 M. Cones. Shorter and thicker receptors. Sensitive at high levels of light. Greatest presence at the Fovea region (sharpest vision). Three types of cones with different wavelength absorption with peaks in the blue, green and red light spectrum Light stimulus activate a rod or cone producing a nerve impulse which is transmitted through the optic nerve. More information at: http://www.vision.ca/eye/lobby.html

  Computer Vision: Applications: Image acquisition Object Recognition. Object Localisation. Advantage: Automatisation. Constraint: Difficult to transmit the human intelligence and skills to a computer. Applications: Shape Inspection for quality control Rapid Prototyping Computer assisted surgery Film making effects Object picking Robot Navigation Image acquisition   Image interpretation

3D Information System selection Modelling Calibration Correspondence Get 3D Cloud Computer vision has become a quite wide research topic, including some interesting fields from image acquisition till scene interpretation. This seminar is focused on getting 3D information which includes the knowledge of all the geometry involved in recovering 3D information. Data Fusion

System Selection Combination of computational and optical techniques aimed at estimating or making explicit geometric (3D shape) properties of objects or scenes from their digital images. stereovision pattern projection laser scanning shape from X (motion, texture, shading, focus, zoom) Computation for all or some pixels of the distance between a known reference frame and the scene point that is imaged in those pixels. The output is a range image (depth map) or a cloud of points {(xi, yi, zi), i=1..N}. The fusion of several range images or point clouds corresponding to partially different views of an object may yield its full 3D digitization.

System Selection Main processes in 3D digitization Range sensing graphic surface solid (triangles) N 3D point clouds Range sensing Geometric fusion Object modeling object solid (splines) best next view System Selection Sensor planning Stereovision Pattern projection Laser scanning Shape from X (motion, texture, shading, focus, zoom) Texture mapping coloured solid

Geometric fusion 24 aligned 3D scans ready for merging set of six 3D scans acquired from different viewpoints and their alignment (center) 24 meshes merged into a surface triangulation.

– Dense reconstruction – Visual inspection Applications – Dense reconstruction – Visual inspection – Object localization – Camera localization P RTH HTC CTW WTR