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Old Projects (before 2005)

Outdoor 3D Scanner Using Off-the-shelf Digital Camera
This project aims at providing a vision based solution for 3D modeling from 2D images. The resulting system could produce photo-realistic 3D models from the 2D photos of real world objects acquired using an off-the-shelf digital camera. Read More...
Tracking of Spinal Motion in Video-fluoroscopy
This project indends to develop a robust a system for analyzing spinal motion in the fluoroscopic video sequence, which is known to have low contrast and varient focus.Read More...

Outdoor 3D Scanner Using Off-the-shelf Digital Camera

The generation of realistic 3D models of real world objects is of great interest in many fields and has many practical applications. For instance, such 3D models can be used in reverse engineering, model-based tracking system, video games, virtual reality, movie making and internet showroom. Traditionally, in computer graphics, such 3D models are constructed using specialized design software in a polygon-by-polygon fashion. Such an approach is very time consuming and the quality of the output model depends very much on the skill of the operator. The introduction of laser scan systems allows 3D objects to be "scanned" into the computer directly, and makes the 3D modeling process faster and easier. In spite of that, such systems are very expensive and require careful calibration before use. Besides, they cannot cope with specular surfaces nor surfaces with low reflectance, and can only handle objects of limited size. This project aims at providing a cost-efficient solution to the above problem through the use of computer vision techniques. Vision-based systems do not require direct mechanical measurements on the objects, and can also handle outdoor objects with various size and reflectance. In this project, the following 2 problems will be addressed:

  • 1. Motion Estimation - The estimation of the relative motion between the object and the camera using features extracted from the images. Most of the existing vision-based techniques use information from the viewpoint independent corner features only, whereas algorithms exploiting the viewpoint dependent silhouettes have only been developed in special cases of constrained motion. The key issue here is to combine the information provided by those 2 complementary sources (i.e. corner features and silhouettes) to provide a robust solution to the motion estimation problem with less constraints placed on the motion itself; and
  • 2. Model Reconstruction - The construction of a 3D model from the image sequence using the estimated/known camera motion and the extracted image features. Existing systems usually produce 3D models composed of extremely large number of triangles. Such models suffer from the geometric aliasing problem and cannot be rendered efficiently. The key issue here is to achieve a smooth, compact and deformable representation for the object model, which can be further refined using other image features available.
  • The results of this research project will provide a robust solution to the structure and motion problem, and thus represent significant original contributions to the study of 3D modeling from 2D images. In addition to original research output, this project also provides a complete framework upon which a practical software for 3D model generation from 2D images can be built. With the decrease in price of digital cameras, such a software system would provide a cheap solution for home users, as well as professionals, to create their own digital archive of 3D models.



    Tracking of Spinal Motion in Video-fluoroscopy

    Low back pain is one of the most common health disorders and its cost is enormous. There is a general consensus that the diagnosis and the treatment of low back pain can be aided by analysing spinal movement. Thus, spinal measurement techniques have been studied widely. At present, videofluoroscopic imaging provides an effective method of obtaining images for spinal motion analysis. Generally, landmarks of a moving vertebra will be extracted from videofluoroscopic video and will then be analysed. Landmarks are usually the corners of the moving vertebra and are usually extracted manually. Unfortunately, the analysis is difficult and time consuming due to the low quality of the videofluoroscopic images. Thus, automatic extraction of landmarks is studied in this project.


    In this project, a method in which an active contour (or snake) will attach to the vertebrae automatically throughout the video sequence is proposed. Users only need to define landmark positions on the first videofluoroscopic image. The active contour formed from such landmarks will attach to the vertebra automatically in the remaining video images. This greatly reduces the effort of physicians in setting accurate landmarks of vertebra manually in every video frame. The reduction in human intervention means the reduction in error rate due to fatigue of the operator. Analysis on spinal motion can be done much more effectively and accurately.