Jalali, S., Tan, C., Lim, J., Tham, J., Ong, S., Seekings, P., & Taylor, E. (2013). Visual Recognition using a Combination of Shape and Color Features. Proceedings of the Annual Meeting of the Cognitive Science Society, 35.
Abstract:
We develop and implement a new approach to utilizing color information for object and scene recognition that is inspired by the characteristics of color- and object-selective neurons in the high-level inferotemporal cortex of the primate visual system. In our hierarchical model, we introduce a new dictionary of features representing visual information as quantized color blobs that preserve coarse, relative spatial information. We run this model on several datasets such as Caltech101, Outdoor Scenes and Underwater Images. The combination of our color features with (grayscale) shape features leads to significant increases in performance over shape or color features alone. Using our model, performance is significantly higher than using color naively, i.e. concatenating the channels of various color spaces. This indicates that usage of color information per se is not enough to produce good performance, and that it is specifically our biologically-inspired approach to color that results in significant improvement.
License type:
Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Funding Info:
There was no specific funding for the research done
Description:
This is the peer reviewed version of the following article: Jalali, S., Tan, C., Lim, J., Tham, J., Ong, S., Seekings, P., & Taylor, E. (2013). Visual Recognition using a Combination of Shape and Color Features. Proceedings of the Annual Meeting of the Cognitive Science Society, 35., which has been published in final form at https://escholarship.org/uc/item/0094h82q . This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.