Abstract
Investigates a measure of "dominant perceived orientation" that has been developed to match the output of a human study involving 40 subjects. The results of this measure are compared with humans analyzing seven "teaser" images to test its effectiveness for finding perceptually dominant orientations. The use of low-level orientation is then applied to a "quick search" problem important in image database applications. Since both pigeons and humans are able to perform coarse classification of certain kinds of scenes, e.g., city from country, without taking time or brain-power to solve the image understanding problem, the authors conjecture that the collective behavior of low-level textural features such as orientation may be doing most of the work. The authors demonstrate a simple test of global multiscale orientation for quickly searching a database of vacation photos for likely "city/suburb" shots. The orientation features achieve agreement with human classification in 91 out of 98 of the scenes.
Keywords
Affiliated Institutions
Related Publications
Identifying High Level Features of Texture Perception
A fundamental issue in texture analysis is that of deciding what textural features are important in texture perception, and how they are used. Experiments on human preattentive ...
Texture synthesis by non-parametric sampling
A non-parametric method for texture synthesis is proposed. The texture synthesis process grows a new image outward from an initial seed, one pixel at a time. A Markov random fie...
Dynamic scene understanding: The role of orientation features in space and time in scene classification
Natural scene classification is a fundamental challenge in computer vision. By far, the majority of studies have limited their scope to scenes from single image stills and there...
SUN database: Large-scale scene recognition from abbey to zoo
Scene categorization is a fundamental problem in computer vision. However, scene understanding research has been constrained by the limited scope of currently-used databases whi...
Unified Perceptual Parsing for Scene Understanding
Humans recognize the visual world at multiple levels: we effortlessly categorize scenes and detect objects inside, while also identifying the textures and surfaces of the object...
Publication Info
- Year
- 2002
- Type
- article
- Volume
- 1
- Pages
- 459-464
- Citations
- 189
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1109/icpr.1994.576325