Active Vision

An approach to active vision based on information theory and statistical mechanics is presented. Density of entropy production measured along a spatio-chromatic diffusion of a colour image is used to build a conspicuity map of the image. The map is successively given as input to a dynamic neural network in order to drive a focus-of-attention scanpath

While it is true that SBM shapes and charts the direction of school operations, it is interesting to discuss how a developing country like the Philippines is influenced by this reform strategy as a structural and procedural framework in managing its system of education, particularly, its basic education sector which through the years has been criticized for its alarming state as shown by its performance indicators rates. This paper purports to provide a panorama on how school-based management as a restructuring framework is viewed and interpreted by the basic education sector which constitutes the largest portion of the country’s educational system. Specifically, the eight key elements of successful SBM schools, namely: (1) an active vision; (2) meaningful decision-making authority; (3) distribution of power; (4) development and use of knowledge and skills; (5) collecting and communicating information; (6) rewards for progress; (7) shared leadership; and (8) cultivating resources, were used to serve the purpose of this discourse.

Can theories of mental imagery, conscious mental contents, developed within cognitive science throw light on the obscure (but culturally very significant) concept of imagination? Three extant views of mental imagery are considered: quasi-pictorial, description, and perceptual activity theories. The first two face serious theoretical and empirical difficulties. The third is (for historically contingent reasons) little known, theoretically underdeveloped, and empirically untried, but has real explanatory potential. It rejects the “traditional” symbolic computational view of mental contents, but is compatible with recent situated cognition and active vision approaches in robotics. This theory is developed and elucidated. Three related key aspects of imagination (non-discursiveness, creativity, and seeing as) raise difficulties for the other theories. Perceptual activity theory presents imagery as non-discursive and relates it closely to seeing as. It is thus well placed to be the basis for a general theory of imagination and its role in creative thought.

Manufacturers often express the performance of a 3D imaging device in various non-uniform ways for the lack of internationally recognized standard requirements for metrological parameters able to identify the capability of capturing a real scene. For this reason several national and international organizations in the last ten years have been developing protocols for verifying such performance. Ranging from VDI/VDE 2634, published by the Association of German Engineers and oriented to the world of mechanical 3D measurements (triangulation-based devices), to the ASTM technical committee E57, working also on laser systems based on direct range detection (TOF, Phase Shift, FM-CW, flash LADAR), this paper shows the state of the art about the characterization of active range devices, with special emphasis on measurement uncertainty, accuracy and resolution. Most of these protocols are based on special objects whose shape and size are certified with a known level of accuracy. By capturing the 3D shape of such objects with a range device, a comparison between the measured points and the theoretical shape they should represent is possible. The actual deviations can be directly analyzed or some derived parameters can be obtained (e.g. angles between planes, distances between barycenters of spheres rigidly connected, frequency domain parameters, etc.). This paper shows theoretical aspects and experimental results of some novel characterization methods applied to different categories of active 3D imaging devices based on both principles of triangulation and direct range detection.

In this article we present a neurally-inspired self-adaptive active binocular tracking scheme and an efficient mathematical model for online computation of desired binocular-head trajectories. The self-adaptive neural network (NN) model is general and can be adopted in output tracking schemes of any partly known robotic systems. The tracking scheme ingeniously combines the conventional Resolved Velocity Control (RVC) technique and an

In this paper a robust system for enabling robots to detect and identify humans in domestic environments is proposed. Robust human detection is achieved through the use of thermal and visual information sources that are integrated to detect human-candidate objects, which are further processed in order to verify the presence of humans and their identity using face information in the thermal and visual spectrums. Face detection is used to verify the presence of humans, and face recognition to identify them. Active vision mechanisms are employed in order to improve the relative pose of a candidate object/person in case direct identification is not possible. The response of the different modules is characterized, and the proposed system is validated using image databases of real domestic environments, and human detection and identification benchmarks of the RoboCup@Home research community.

The empirical investigation of cognitive processes in infants is hampered by the limited development of their body and motor control skills. Novel gaze-contingent paradigms, where infants control their environment with their eyes, offer a solution to this problem since the control of gaze develops very early. Recently such a paradigm has been used to investigate the learning of anticipatory behaviour of 6/8-months-old infants in an experiment where gazing at a ``button'' causes the appearance of an interesting image.
The experiment shows that infants learn in few trials to ``press the button'' with their gaze and, remarkably, to anticipate the image appearance.
The experiment raises two questions:
(a) what are the processes supporting such fast learning?
(b) why does the anticipatory behaviour emerge?
This paper presents a bio-inspired model that puts forward possible answers to these questions.
The model consists of:
(a) a bottom-up attention component for scene saliency detection;
(b) a top-down attention component that uses reinforcement learning (RL) to learn to control gaze based on current foveal stimuli;
(c) a dynamic field map that decides where to look based on the bottom-up and top-down information.
The results show that the model is indeed capable of learning to perform anticipatory saccades in few trials.
The analysis of the system shows that this fast learning is due to the guidance exerted by the bottom-up component on the learning process of the top-down component.
Moreover, it shows that the anticipatory behaviour can be explained in terms of the action of the top-down component exploiting the learned spatial relations of stimuli in an anticipatory fashion.
Overall, the results indicate that the model has the essential features to theoretically frame, interpret, and design experiments based on the gaze-contingent paradigm.

The European Space Agency (ESA) is preparing for unmanned and/or manned exploration of several planets including Mercury and Mars. To support this endeavour several key technologies have to be developed. Among these necessary technologies are navigation sensors that can support landing and sample-return capsule rendezvous operations. A vision-based navigation sensor is currently being developed by ESA [1] which will enable surface relative navigation. The Planet and Asteroid Natural-scene Generation Utility (PANGU) is a system for generating simulated surfaces of planets and for producing images of those surfaces from specified camera positions and orientations [2][3][4][5][6][7]. PANGU was implemented specifically to support the development of vision-based navigation sensors and is now being used to validate associated image feature tracking algorithms. Vision-based sensors that use passive vision are only suitable for a landing on the sunlit side of a planet, unless the spacecraft contains an illumination source. Active vision sensors, particularly LIDAR, are suitable for lander navigation on the sunlit or dark side of a planet. They are also suitable for use on dimly sunlit objects such as asteroids. The planetary surfaces generated by PANGU are ideal for supporting the development and testing of LIDAR sensors and related signal processing techniques. In this case the camera model within PANGU that provides images of the surface is replaced by a LIDAR sensor model. This paper describes current research at the University of Dundee which is extending the capabilities of the PANGU tool to include LIDAR simulation. Effort is focused on the landing and rendezvous phases of planetary missions and the use of LIDAR to support the GNC function during these dangerous parts of the mission.

This dissertation describes a new approach to visual tracking for monocular and binocular image sequences, and for both passive and active cameras. The method combines Kalman-type prediction with steepest-descent search for correspondences, using 2-dimensional affine mappings ...

Vergence provides robot vision systems with a crucial degree of freedom: it enables fixation of points in visual space at different distances from the observer. Vergence control, therefore, affects the performance of the stereo system as well as the results of motion estimation and tracking and, as such, must satisfy different requirements in order to be able to provide not only a stable fixation, but a stable binocular fusion, and a fast, smooth and accurate reaction to changes in the environment. To obtain this kind of performance the paper focuses specifically on the use of dynamic visual information to drive vergence control. In this context, moreover, the use of a space-variant, anthropomorphic sensor is described and some advantages in relation to vergence control are discussed to demonstrate the relevance of image plane geometry for this particular task. Expansion or contraction patterns and the temporal evolution of the degree of fusion measured in the log-polar domain are the inputs to the vergence control system and determine robust and accurate steering of the two cameras. Real-time experiments are presented to demonstrate the performance of the system covering different key situations.

ABSTRACT Manufacturers often express the performance of a 3D imaging device in various non-uniform ways for the lack of internationally recognized standard requirements for metrological parameters able to identify the capability of capturing a real scene. For this reason several national and international organizations in the last ten years have been developing protocols for verifying such performance. Ranging from VDI/VDE 2634, published by the Association of German Engineers and oriented to the world of mechanical 3D measurements (triangulation-based devices), to the ASTM technical committee E57, working also on laser systems based on direct range detection (TOF, Phase Shift, FM-CW, flash LADAR), this paper shows the state of the art about the characterization of active range devices, with special emphasis on measurement uncertainty, accuracy and resolution. Most of these protocols are based on special objects whose shape and size are certified with a known level of accuracy. By capturing the 3D shape of such objects with a range device, a comparison between the measured points and the theoretical shape they should represent is possible. The actual deviations can be directly analyzed or some derived parameters can be obtained (e.g. angles between planes, distances between barycenters of spheres rigidly connected, frequency domain parameters, etc.). This paper shows theoretical aspects and experimental results of some novel characterization methods applied to different categories of active 3D imaging devices based on both principles of triangulation and direct range detection.