Condensation algorithm
Encyclopedia
The condensation algorithm (Conditional Density Propagation) is a computer vision
algorithm. The principal application is to detect and track
the contour of objects moving in a cluttered environment. Object tracking is one of the more basic and difficult aspects of computer vision and is generally a prerequisite to object recognition. Being able to identify which pixels in an image make up the contour of an object is a non-trivial problem. Condensation is a probabilistic algorithm that attempts to solve this problem.
The algorithm itself is described in detail by Isard and Blake
in a publication in the International Journal of Computer Vision in 1998. One of the most interesting facets of the algorithm is that it does not compute on every pixel of the image. Rather, pixels to process are chosen at random, and only a subset of the pixels end up being processed. Multiple hypotheses about what is moving where are supported naturally by the probabilistic nature of the approach. The evaluation functions come largely from previous work in the area and include many standard statistical approaches. The original part of this work is the application of particle filter estimation techniques.
Computer vision
Computer vision is a field that includes methods for acquiring, processing, analysing, and understanding images and, in general, high-dimensional data from the real world in order to produce numerical or symbolic information, e.g., in the forms of decisions...
algorithm. The principal application is to detect and track
Video tracking
Video tracking is the process of locating a moving object over time using a camera. It has a variety of uses, some of which are: human-computer interaction, security and surveillance, video communication and compression, augmented reality, traffic control, medical imaging and video editing...
the contour of objects moving in a cluttered environment. Object tracking is one of the more basic and difficult aspects of computer vision and is generally a prerequisite to object recognition. Being able to identify which pixels in an image make up the contour of an object is a non-trivial problem. Condensation is a probabilistic algorithm that attempts to solve this problem.
The algorithm itself is described in detail by Isard and Blake
Andrew Blake (scientist)
Andrew Blake, FREng, FRS, is a British scientist, Managing Director of Microsoft Research Cambridge, Distinguished Visiting Professor at the University of Edinburgh, and a leading researcher in computer vision.-Career:...
in a publication in the International Journal of Computer Vision in 1998. One of the most interesting facets of the algorithm is that it does not compute on every pixel of the image. Rather, pixels to process are chosen at random, and only a subset of the pixels end up being processed. Multiple hypotheses about what is moving where are supported naturally by the probabilistic nature of the approach. The evaluation functions come largely from previous work in the area and include many standard statistical approaches. The original part of this work is the application of particle filter estimation techniques.
See also
- Particle filterParticle filterIn statistics, particle filters, also known as Sequential Monte Carlo methods , are sophisticated model estimation techniques based on simulation...
- Condensation is the application of Sampling Importance Resampling (SIR) estimation to contour tracking
External links
- Condensation homepage
- Condensation - conditional density propagation for visual tracking, by Michael Isard and Andrew Blake (International Journal of Computer Vision 29(1):5-28, August 1998)