Combined Object Categorization and Segmentation With an Implicit Shape Model
ETH Zurich · University of Ljubljana
Abstract
We present a method for object categorization in real-world scenes. Following a common consensus in the field, we do not assume that a figure-ground segmentation is available prior to recognition. However, in contrast to most standard approaches for object class recognition, our approach automatically segments the object as a result of the categorization. This combination of recognition and segmentation into one process is made possible by our use of an Implicit Shape Model, which integrates both capabilities into a common probabilistic framework. In addition to the recognition and segmentation result, it also generates a per-pixel confidence measure specifying the area that supports a hypothesis and how much…
Citation impact
- FWCI
- 34.23
- Percentile
- 100%
- References
- 27
Authors
3Topics & keywords
- Categorization
- Segmentation
- Artificial intelligence
- Computer science
- Object (grammar)
- Pattern recognition (psychology)
- Probabilistic logic
- Contrast (vision)