title: A novel biologically inspired local feature descriptor.
abstract: Local feature descriptor is a fundamental representation for image patch which has been extensively used in many computer vision applications. In this paper, different from state-of-the-art features, a novel biologically inspired local descriptor (BILD) is proposed based on the visual information processing mechanism of ventral pathway in human brain. The local features used for constructing BILD are extracted by a two-layer network, which corresponds to the simple-to-complex cell hierarchy in the primary visual cortex (V1). It works in a similar way as the simple cell and complex cell do to get responses by applying the lateral inhibition from different orientations and operating an improved cortical pooling. To enhance the distinctiveness of BILD, we combine the local features from different orientations. Extensive evaluations have been performed for image matching and object recognition. Experimental results reveal that our proposed BILD outperforms many widely used descriptors such as SIFT and SURF, which demonstrate its efficiency for representing local regions.
authors.affiliation: National Key Laboratory of Science and Technology on Multi-spectral Information Processing, School of Automation, Huazhong University of Science and Technology, Wuhan, 430074, China, zhangyun.2010@foxmail.com.
authors.forename: Yun
authors.initials: Y
authors.lastname: Zhang
authors.forename: Tian
authors.initials: T
authors.lastname: Tian
authors.forename: Jinwen
authors.initials: J
authors.lastname: Tian
authors.forename: Junbin
authors.initials: J
authors.lastname: Gong
authors.forename: Delie
authors.initials: D
authors.lastname: Ming
mesh_terms: D000818:Animals; D003198:Computer Simulation; D006801:Humans; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D014793:Visual Cortex; D014796:Visual Perception