Biologically Inspired Vision for Indoor Robot Navigation

Ultrasonic, infrared, laser and other sensors are being applied in robotics. Although combinations of these have allowed robots to navigate, they are only suited for specific scenarios, depending on their limitations. Recent advances in computer vision are turning cameras into useful low-cost sensors that can operate in most types of environments. Cameras enable robots to detect obstacles, recognize objects, obtain visual odometry, detect and recognize people and gestures, among other possibilities. In this paper we present a completely biologically inspired vision system for robot navigation. It comprises stereo vision for obstacle detection, and object recognition for landmark-based navigation. We employ a novel keypoint descriptor which codes responses of cortical complex cells. We also present a biologically inspired saliency component, based on disparity and colour.

The smart vision local navigation aid for blind and visually impaired persons

The SmartVision prototype is a small, cheap and easily wearable navigation aid for blind and visually impaired persons. Its functionality addresses global navigation for guiding the user to some destiny, and local navigation for negotiating paths, sidewalks and corridors, with avoidance of static as well as moving obstacles. Local navigation applies to both in- and outdoor situations. In this article we focus on local navigation: the detection of path borders and obstacles in front of the user and just beyond the reach of the white cane, such that the user can be assisted in centering on the path and alerted to looming hazards. Using a stereo camera worn at chest height, a portable computer in a shoulder-strapped pouch or pocket and only one earphone or small speaker, the system is inconspicuous, it is no hindrence while walking with the cane, and it does not block normal surround sounds. The vision algorithms are optimised such that the system can work at a few frames per second.

Painterly rendering using human vision

Painterly rendering has been linked to computer vision, but we propose to link it to human vision because perception and painting are two processes that are interwoven. Recent progress in developing computational models allows to establish this link. We show that completely automatic rendering can be obtained by applying four image representations in the visual system: (1) colour constancy can be used to correct colours, (2) coarse background brightness in combination with colour coding in cytochrome-oxidase blobs can be used to create a background with a big brush, (3) the multi-scale line and edge representation provides a very natural way to render fi ner brush strokes, and (4) the multi-scale keypoint representation serves to create saliency maps for Focus-of-Attention, and FoA can be used to render important structures. Basic processes are described, renderings are shown, and important ideas for future research are discussed.

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.

A vision fronted with a new disparity model

We are developing a frontend that is based on the image representation in the visual cortex and plausible processing schemes. This frontend consists of multiscale line/edge and keypoint (vertex) detection, using models of simple, complex and end-stopped cells. This frontend is being extended by a new disparity model. Assuming that there is no neural inverse tangent operator, we do not exploit Gabor phase information. Instead, we directly use simple cell (Gabor) responses at positions where lines and edges are detected.

Integrated multi-scale architecture of the cortex with application to computer vision

Tese de dout., Engenharia Electrónica e de Computadores, Faculdade de Ciência e Tecnologia, Universidade do Algarve, 2007

A vision system for detecting paths and moving obstacles for the blind

In this paper we present a monocular vision system for a navigation aid. The system assists blind persons in following paths and sidewalks, and it alerts the user to moving obstacles which may be on collision course. Path borders and the vanishing point are de-tected by edges and an adapted Hough transform. Opti-cal flow is detected by using a hierarchical, multi-scale tree structure with annotated keypoints. The tree struc-ture also allows to segregate moving objects, indicating where on the path the objects are. Moreover, the centre of the object relative to the vanishing point indicates whether an object is approaching or not.

Local gist vision of man-made objects

Attention is usually modelled by sequential fixation of peaks in saliency maps. Those maps code local conspicuity: complexity, colour and texture. Such features have no relation to entire objects, unless also disparity and optical flow are considered, which often segregate entire objects from their background. Recently we developed a model of local gist vision: which types of objects are about where in a scene. This model addresses man-made objects which are dominated by a small shape repertoire: squares, rectangles, trapeziums, triangles, circles and ellipses. Only exploiting local colour contrast, the model can detect these shapes by a small hierarchy of cell layers devoted to low- and mid-level geometry. The model has been tested successfully on video sequences containing traffic signs and other scenes, and partial occlusions were not problematic.

Object segregation and local gist vision using low-level geometry

Multi-scale representations of lines, edges and keypoints on the basis of simple, complex and end-stopped cells can be used for object categorisation and recognition (Rodrigues and du Buf, 2009 BioSystems 95 206-226). These representations are complemented by saliency maps of colour, texture, disparity and motion information, which also serve to model extremely fast gist vision in parallel with object segregation. We present a low-level geometry model based on a single type of self-adjusting grouping cell, with a circular array of dendrites connected to edge cells located at several angles.

A computer vision based web application for tracking soccer players

Soccer is a sport where everyone that is involved with it make all the efforts aiming for excellence. Not only the players need to show their skills on the pitch but also the coach, and the remaining staff, need to have their own tools so that they can perform at higher levels. Footdata is a project to build a new web application product for soccer (football), which integrates two fundamental components of this sport's world: the social and the professional. While the former is an enhanced social platform for soccer professionals and fans, the later can be considered as a Soccer Resource Planning, featuring a system for acquisition and processing information to meet all the soccer management needs. In this paper we focus only in a specific module of the professional component. We will describe the section of the web application that allows to analyse movements and tactics of the players using images directly taken from the pitch or from videos, we will show that it is possible to draw players and ball movements in a web application and detect if those movements occur during a game. © 2014 Springer International Publishing.

A computer vision based web application for tracking soccer players

Soccer is a sport where everyone that is involved with it make all the efforts aiming for excellence. Not only the players need to show their skills on the pitch but also the coach, and the remaining staff, need to have their own tools so that they can perform at higher levels. Footdata is a project to build a new web application product for soccer (football), which integrates two fundamental components of this sport’s world: the social and the professional. While the former is an enhanced social platform for soccer professionals and fans, the later can be considered as a Soccer Resource Planning, featuring a system for acquisition and processing information to meet all the soccer management needs. In this paper we focus only in a specific module of the professional component. We will describe the section of the web application that allows to analyse movements and tactics of the players using images directly taken from the pitch or from videos, we will show that it is possible to draw players and ball movements in a web application and detect if those movements occur during a game.