Object categorisations using templates constructed from multi-scale line and edge representations

Object categorisation is linked to detection, segregation and recognition. In the visual system, these processes are achieved in the ventral \what"and dorsal \where"pathways [3], with bottom-up feature extractions in areas V1, V2, V4 and IT (what) in parallel with top-down attention from PP via MT to V2 and V1 (where). The latter is steered by object templates in memory, i.e. in prefrontal cortex with a what component in PF46v and a where component in PF46d.

Face segregation and recognition by cortical multi-scale line and edge coding

Models of visual perception are based on image representations in cortical area V1 and higher areas which contain many cell layers for feature extraction. Basic simple, complex and end-stopped cells provide input for line, edge and keypoint detection. In this paper we present an improved method for multi-scale line/edge detection based on simple and complex cells. We illustrate the line/edge representation for object reconstruction, and we present models for multi-scale face (object) segregation and recognition that can be embedded into feedforward dorsal and ventral data streams (the “what” and “where” subsystems) with feedback streams from higher areas for obtaining translation, rotation and scale invariance.

Face recognition by cortical multi-scale line and edge representations

Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. Models of visual perception are based on image representations in cortical area V1 and beyond, which contain many cell layers for feature extraction. Simple, complex and end-stopped cells provide input for line, edge and keypoint detection. Detected events provide a rich, multi-scale object representation, and this representation can be stored in memory in order to identify objects. In this paper, the above context is applied to face recognition. The multi-scale line/edge representation is explored in conjunction with keypoint-based saliency maps for Focus-of-Attention. Recognition rates of up to 96% were achieved by combining frontal and 3/4 views, and recognition was quite robust against partial occlusions.

Improved line/edge detection and visual reconstruction

Lines and edges provide important information for object categorization and recognition. In addition, one brightness model is based on a symbolic interpretation of the cortical multi-scale line/edge representation. In this paper we present an improved scheme for line/edge extraction from simple and complex cells and we illustrate the multi-scale representation. This representation can be used for visual reconstruction, but also for nonphotorealistic rendering. Together with keypoints and a new model of disparity estimation, a 3D wireframe representation of e.g. faces can be obtained in the future.

Cortical object segregation and categorization by multi-scale line and edge coding

In this paper we present an improved scheme for line and edge detection in cortical area V1, based on responses of simple and complex cells, truly multi-scale with no free parameters. We illustrate the multi-scale representation for visual reconstruction, and show how object segregation can be achieved with coarse-to-finescale groupings. A two-level object categorization scenario is tested in which pre-categorization is based on coarse scales only, and final categorization on coarse plus fine scales. Processing schemes are discussed in the framework of a complete cortical architecture.

Recognition of facial expressions by cortical multi-scale line and edge coding

Empirical studies concerning face recognition suggest that faces may be stored in memory by a few canonical representations. Models of visual perception are based on image representations in cortical area V1 and beyond, which contain many cell layers for feature extraction. Simple, complex and end-stopped cells provide input for line, edge and keypoint detection. Detected events provide a rich, multi-scale object representation, and this representation can be stored in memory in order to identify objects. In this paper, the above context is applied to face recognition. The multi-scale line/edge representation is explored in conjunction with keypoint-based saliency maps for Focus-of-Attention. Recognition rates of up to 96% were achieved by combining frontal and 3/4 views, and recognition was quite robust against partial occlusions.

A disparity energy model improved by line, edge and keypoint correspondences

Disparity energy models (DEMs) estimate local depth information on the basis ofVl complex cells. Our recent DEM (Martins et al, 2011 ISSPlT261-266) employs a population code. Once the population's cells have been trained with randorn-dot stereograms, it is applied at all retinotopic positions in the visual field. Despite producing good results in textured regions, the model needs to be made more precise, especially at depth transitions.

Genetic structure at range edge: Low diversity and high inbreeding in Southeast Asian mangrove (Avicennia marina) populations

Understanding the genetic composition and mating systems of edge populations provides important insights into the environmental and demographic factors shaping species’ distribution ranges. We analysed samples of the mangrove Avicennia marina from Vietnam, northern Philippines and Australia, with microsatellite markers. We compared genetic diversity and structure in edge (Southeast Asia, and Southern Australia) and core (North and Eastern Australia) populations, and also compared our results with previously published data from core and southern edge populations. Comparisons highlighted significantly reduced gene diversity and higher genetic structure in both margins compared to core populations, which can be attributed to very low effective population size, pollinator scarcity and high environmental pressure at distribution margins. The estimated level of inbreeding was significantly higher in northeastern populations compared to core and southern populations. This suggests that despite the high genetic load usually associated with inbreeding, inbreeding or even selfing may be advantageous in margin habitats due to the possible advantages of reproductive assurance, or local adaptation. The very high level of genetic structure and inbreeding show that populations of A. marina are functioning as independent evolutionary units more than as components of a metapopulation system connected by gene flow. The combinations of those characteristics make these peripheral populations likely to develop local adaptations and therefore to be of particular interest for conservation strategies as well as for adaptation to possible future environmental changes.