CVGResearch

Home
3D Reconstruction
Texture Analysis
Shape Analysis
Segmentation
Recognition
Fractal Graphics
Members

Computer Vision and Graphics   中文

3D Reconstruction We live in a three-dimensional world (evolving with the elapsing time) and possess stereo vision thanks to the pair of our eyes (and our brain). Inspired by this natural endowment, a central problem of computer vision is to obtain 3D geometric shape information of the objects from planar images. This process is traditionally termed 3D reconstruction. 3D reconstruction of the objects and environments is useful in itself as it amounts to obtaining their 3D geometric measurement (termed 3D models in graphics community), and is also a helpful means for object recognition since it eliminates the headache-causing variances produced by the perspective imaging process and variable illumination.
Texture Analysis The unevenness patterns of the pixel attributes in a region give rise to the visual perception of image texture. Texture reflects the variations of the optical properties of object surfaces and illumination. Different materials usually produce distinctive surface texture. This makes image texture an important source of discriminant information. Texture plays an important role in various recognition applications such as product surface inspection, identification of objects in images, image based medical screening and diagnosis.
Shape Analysis Different objects typically posses distinctive shapes. This makes shape an important discriminant feature for object description and recognition. Some shapes are instinctively planar such as those of alphabets and words while many others are 3D in nature. Shape analysis is key to many applications such as character recognition, symbol classification and retrieval, object recognition and retrieval.
Segmentation Natural and man-made scenes are often made up of components, and some components can further be divided into smaller constituent elements, and so on. This hierarchical organization naturally motivates the study of segmentation, that is, an image of scenes and objects (as well as their 3D reconstructed models) can be beneficially segmented into meaningful parts. Automatic segmentation using the computer is useful in itself, and is also (debatably) widely considered as an important intermediate step for scene analysis and recognition.
Recognition Objects tend to fall into categories. Those of the same class usually share common features while those of different classes possess distinctive features, which makes recognition possible. A key (futuristic) goal of computer vision is to empower the machine with the superb recognition ability of the human vision system. Object recognition has found many successful applications such as character, fingerprint, face recognition, and also plays a key role in many fields such as video surveillance and remote sensing, product inspection, biological research and medical diagnosis.
Fractal Graphics How much does mathematics relate to arts? The answer becomes more positive after you have seen the beauty of the scenes created by fractals.
More...

Updated. June 2008