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.

An integrated framework for combining gist vision with object segregation categorisation and recognition

There are roughly two processing systems: (1) very fast gist vision of entire scenes, completely bottom-up and data driven, and (2) Focus-of-Attention (FoA) with sequential screening of specific image regions and objects. The latter system has to be sequential because unnormalised input objects must be matched against normalised templates of canonical object views stored in memory, which involves dynamic routing of features in the visual pathways.

Simple brightness models with low-pass and Gabor filters

A syntactical brightness model based on a multiscale line and edge representation obtained by a set of anisotropic Gabor filters is quite complex (du Buf and Fischer, 1995 Optical Engineering 34 1900-1911). Although only tested in 1-D, it was shown to yield correct brightness effects for many patterns.

Face normalization using multi-scale cortical keypoints

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 extractions. Simple, complex and end-stopped cells tuned to different spatial frequencies (scales) and/or orientations provide input for line, edge and keypoint detection. This yields a rich, multi-scale object representation that can be stored in memory in order to identify objects. The multi-scale, keypoint-based saliency maps for Focus-of-Attention can be explored to obtain face detection and normalization, after which face recognition can be achieved using the line/edge representation. In this paper, we focus only on face normalization, showing that multi-scale keypoints can be used to construct canonical representations of faces in memory.

Multi-scale keypoint hierarchy for Focus-of-Attention and object detection

Hypercolumns in area V1 contain frequency- and orientation-selective simple and complex cells for line (bar) and edge coding, plus end-stopped cells for key- point (vertex) detection. A single-scale (single-frequency) mathematical model of single and double end-stopped cells on the basis of Gabor filter responses was developed by Heitger et al. (1992 Vision Research 32 963-981). We developed an improved model by stabilising keypoint detection over neighbouring micro- scales.

Fine arts edutainment: the amateur painter

A new scheme for painterly rendering (NPR) has been developed. This scheme is based on visual perception, in particular themulti-scale line/edge representation in the visual cortex. The Amateur Painter (TAP) is the user interface on top of the rendering scheme. It allows to (semi)automatically create paintings from photographs, with different types of brush strokes and colour manipulations. In contrast to similar painting tools, TAP has a set of menus that reflects the procedure followed by a normal painter. In addition, menus and options have been designed such that they are very intuitive, avoiding a jungle of sub-menus with options from image processing that children and laymen do not understand. Our goal is to create a tool that is extremely easy to use, with the possibility that the user becomes interested in painting techniques, styles, and fine arts in general.

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.

Blavigator: a navigation aid for blind persons

Blavigator (blind navigator) is a vision aid for blind and visuaIIy impaired persons. It supports local navigation by detecting waIkable paths in the immediate vicinity of the user. It guides the user for centering on the path.

Fast and accurate multi-scale keypoints based on end-stopped cells

Increasingly more applications in computer vision employ interest points. Algorithms like SIFT and SURF are all based on partial derivatives of images smoothed with Gaussian filter kemels. These algorithrns are fast and therefore very popular.

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.

Visuoperceptual deficits and participation in older adults after stroke

Introduction: Visuoperceptual deficits frequently occur after a stroke but little is known about how they evolve over time. These deficits may have an impact on participation in daily activities and social roles. Objectives: The aims were to 1) track changes over six months in the visual perception of older adults with persistent visuoperceptual deficits after a stroke; 2) examine if these changes differed between participants who had and had not received rehabilitation services; and 3) verify if participation differed between participants with and without visuoperceptual deficits. Methods: Visual perception as well as participation of 189 older adults who had had a stroke were evaluated in the first month (T1) after being discharged home from an acute care hospital (NO REHAB group) or rehabilitation unit (REHAB group). For visual perception, only participants presenting deficits at T1 were re-evaluated at 3 months (T2; n=93), and those with deficits at T2 were re-evaluated at 6 months (T3; n=61). Results: A total of 57 people (30.2%) had visuoperceptual deficits six months after discharge home. Despite persistent deficits, approximately 45% of the participants in the two groups improved while 50% of the NO REHAB group and 24.3% of the REHAB group deteriorated. Changes in the mean scores on the MVPT-V were similar in the two groups. Participation, and especially participation in social roles, was more restricted in participants with visuoperceptual deficits (p<0.001), whatever the severity of the stroke. Conclusion: Visuoperceptual deficits are common post-stroke. However, they evolve differently in different people and are associated with a reduction in participation.

Modelfest and contrast-interrelation-function data predicted by a retinal model

The automatic implementation of decoders for a visual perception is achieved as follows. The action described by a production rule is realized by means of the decoder in which a pattern of connections coreesponds to that of stimuli. According to "S.Karasawa,(Proc. of CCCT, Vol.5, pp.194-1999, Austin, Texas, August, 2004)", each program mable controllable connection among inputs is realized by a floating gate avalanche injection MOS FET, where inverted signals are used at writing, and the detection of matching between inputs and connections is carried out by using the signal source in which low level signal is provided via comparatively smaller resistance than high level.

O lugar e o objeto como circunstância do esquisso

Tese de doutoramento, Belas-Artes (Desenho), Universidade de Lisboa, Faculdade de Belas-Artes, 2016

Tratamento de cor em pós-produção televisiva: o caso da produtora de conteúdos SP Televisão

Dissertação apresentada à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.

Retratos de um Bairro : a fotografia como forma de comunicação

Trabalho de projeto apresentado à Escola Superior de Comunicação Social como parte dos requisitos para obtenção de grau de mestre em Audiovisual e Multimédia.