Sex differences: From mental rotation to object location memory, an ERP study

Sex differences in cognition have been largely investigated. The most consistent sex differences favoring females are observed in object location memory involving the left hemisphere whereas the most consistent sex differences favoring males are observed in tasks that require mental rotation involving the right hemisphere. Here we used a task involving these two abilities to see the impact of mental rotation on object location memory. To that end we used a combination of behavioral and event-related potential (ERP) electroencephalography (EEG) measures.A computer screen displayed a square frame of 4 pairs of images (a "teddy" bear, a shoe, an umbrella and a lamp) randomly arranged around a central fixation cross. After a 10-second interval for memorization, images disappeared and were replaced by a test frame with no image but a random pair of two locations marked in black. In addition, this test frame was randomly displayed either in the original orientation (0° rotation) or in the rotated one (90° clockwise - CW - or 90° counterclockwise - CCW). Preceding the test frame, an arrow indicating the presence or the absence of rotation of the frame was displayed on the screen. The task of the participants (15 females and 15 males) was to determine if two marked locations corresponded or not to a pair of identical images. Each response was followed by feedback.Findings showed no significant sex differences in the performance of the original orientation. In comparison with this position, the rotation of the frame produced an equal decrease of male and female performance. In addition, this decrease was significantly higher when the rotation of the frame was in a CCW direction. We further assessed the ERP when the arrow indicated the direction of rotation as stimulus-onset, during four time windows representing major components C1, P1, N1 and N2. Although no sex differences were observed in performance, brain activities differed according to sex. Enhanced amplitudes were found for the CCW compared to CW rotation over the right posterior areas for the P1, N1 and N2 components for men as well as for women. Major topographical differences related to sex were measured for the CW rotation condition as marked lateralized amplitude: left-hemisphere amplitude larger than right one was measured during P1 time range for men. These similar patterns prolonged from P1 to N1 for women. Early distinctions were found in interaction with sex between CCW and CW waveform amplitudes, expressing over anterior electrode sites during C1 time range (0-50 ms post-stimulus).In conclusion (i) women do not outperform men in object location memory in this study (absence of rotation condition); (ii) mental rotation, in particular the direction of rotation, influences performance on object location memory; (iii) CCW rotation is associated with activity in the right parietal hemisphere whereas the CW rotation involves the left parietal hemisphere; (iv) this last effect is less pronounced in males, which could explain why greater involvement of right parietal areas in men and of bilateral posterior areas in women is generally reported in mental rotation tasks; and (v) the early distinctions between both directions of rotation located over anterior sites could be related to sex differences in their respective involvement of control mechanisms.

The Reflections of Strategic Orientation on profitability - A resource-based study in pulp and paper industry

Tutkielman tavoitteena oli analysoida erilaisia strategisia orientaatioita sellu- ja paperiteollisuudessa. Sellu- ja paperiteollisuus on kohtaamassa strategisia haasteita, jotka ulottuvat syvälle sen rakenteisiin. Yritykset ovat valinneet erilaisia lähestymistapoja organisoidessaan tuotantoa ja kansainvälistä arvoketjuaan tässä muuttuvassa ympäristössä. Tutkimukseen valittiin 30 suurinta sellu- ja paperiteollisuudessa toimivaa yritystä ja mahdollisia syitä kannattavuuseroihin yritysten välillä analysoitiin. Yritysten strategista orientaatiota tarkasteltiin vertailemalla muun muassa seuraavia tekijöitä: vertikaalinen integraatioaste, tuotevalikoiman laajuus, tuotantokapasiteetin levinneisyys ja tuotantokapasiteetin ikä. Kannattavuutta mitattiin erilaisilla talouden tunnusluvuilla (liikevoitto, oman pääoman tuotto-%, koko pääoman tuotto-%). Tulosten mukaan yrityksiä voidaan ryhmitellä strategisen orientaation perusteella ja ryhmien välillä on kannattavuuseroja.

Probabilistic position and orientation estimation of rigid objects using an RGB-D sensor

The recent emergence of low-cost RGB-D sensors has brought new opportunities for robotics by providing affordable devices that can provide synchronized images with both color and depth information. In this thesis, recent work on pose estimation utilizing RGBD sensors is reviewed. Also, a pose recognition system for rigid objects using RGB-D data is implemented. The implementation uses half-edge primitives extracted from the RGB-D images for pose estimation. The system is based on the probabilistic object representation framework by Detry et al., which utilizes Nonparametric Belief Propagation for pose inference. Experiments are performed on household objects to evaluate the performance and robustness of the system.

Generative Part-Based Gabor Object Detector

Object detection is a fundamental task of computer vision that is utilized as a core part in a number of industrial and scientific applications, for example, in robotics, where objects need to be correctly detected and localized prior to being grasped and manipulated. Existing object detectors vary in (i) the amount of supervision they need for training, (ii) the type of a learning method adopted (generative or discriminative) and (iii) the amount of spatial information used in the object model (model-free, using no spatial information in the object model, or model-based, with the explicit spatial model of an object). Although some existing methods report good performance in the detection of certain objects, the results tend to be application specific and no universal method has been found that clearly outperforms all others in all areas. This work proposes a novel generative part-based object detector. The generative learning procedure of the developed method allows learning from positive examples only. The detector is based on finding semantically meaningful parts of the object (i.e. a part detector) that can provide additional information to object location, for example, pose. The object class model, i.e. the appearance of the object parts and their spatial variance, constellation, is explicitly modelled in a fully probabilistic manner. The appearance is based on bio-inspired complex-valued Gabor features that are transformed to part probabilities by an unsupervised Gaussian Mixture Model (GMM). The proposed novel randomized GMM enables learning from only a few training examples. The probabilistic spatial model of the part configurations is constructed with a mixture of 2D Gaussians. The appearance of the parts of the object is learned in an object canonical space that removes geometric variations from the part appearance model. Robustness to pose variations is achieved by object pose quantization, which is more efficient than previously used scale and orientation shifts in the Gabor feature space. Performance of the resulting generative object detector is characterized by high recall with low precision, i.e. the generative detector produces large number of false positive detections. Thus a discriminative classifier is used to prune false positive candidate detections produced by the generative detector improving its precision while keeping high recall. Using only a small number of positive examples, the developed object detector performs comparably to state-of-the-art discriminative methods.

Video Object Tracking And Analysis For Computer Assisted Surgery

Pedicle screw insertion technique has made revolution in the surgical treatment of spinal fractures and spinal disorders. Although X- ray fluoroscopy based navigation is popular, there is risk of prolonged exposure to X- ray radiation. Systems that have lower radiation risk are generally quite expensive. The position and orientation of the drill is clinically very important in pedicle screw fixation. In this paper, the position and orientation of the marker on the drill is determined using pattern recognition based methods, using geometric features, obtained from the input video sequence taken from CCD camera. A search is then performed on the video frames after preprocessing, to obtain the exact position and orientation of the drill. An animated graphics, showing the instantaneous position and orientation of the drill is then overlaid on the processed video for real time drill control and navigation

The Use of Grouping in Visual Object Recognition.

The report describes a recognition system called GROPER, which performs grouping by using distance and relative orientation constraints that estimate the likelihood of different edges in an image coming from the same object. The thesis presents both a theoretical analysis of the grouping problem and a practical implementation of a grouping system. GROPER also uses an indexing module to allow it to make use of knowledge of different objects, any of which might appear in an image. We test GROPER by comparing it to a similar recognition system that does not use grouping.

Attentional Selection in Object Recognition

A key problem in object recognition is selection, namely, the problem of identifying regions in an image within which to start the recognition process, ideally by isolating regions that are likely to come from a single object. Such a selection mechanism has been found to be crucial in reducing the combinatorial search involved in the matching stage of object recognition. Even though selection is of help in recognition, it has largely remained unsolved because of the difficulty in isolating regions belonging to objects under complex imaging conditions involving occlusions, changing illumination, and object appearances. This thesis presents a novel approach to the selection problem by proposing a computational model of visual attentional selection as a paradigm for selection in recognition. In particular, it proposes two modes of attentional selection, namely, attracted and pay attention modes as being appropriate for data and model-driven selection in recognition. An implementation of this model has led to new ways of extracting color, texture and line group information in images, and their subsequent use in isolating areas of the scene likely to contain the model object. Among the specific results in this thesis are: a method of specifying color by perceptual color categories for fast color region segmentation and color-based localization of objects, and a result showing that the recognition of texture patterns on model objects is possible under changes in orientation and occlusions without detailed segmentation. The thesis also presents an evaluation of the proposed model by integrating with a 3D from 2D object recognition system and recording the improvement in performance. These results indicate that attentional selection can significantly overcome the computational bottleneck in object recognition, both due to a reduction in the number of features, and due to a reduction in the number of matches during recognition using the information derived during selection. Finally, these studies have revealed a surprising use of selection, namely, in the partial solution of the pose of a 3D object.

Investigating shape representation in area V4 with HMAX: Orientation and Grating selectivities

The question of how shape is represented is of central interest to understanding visual processing in cortex. While tuning properties of the cells in early part of the ventral visual stream, thought to be responsible for object recognition in the primate, are comparatively well understood, several different theories have been proposed regarding tuning in higher visual areas, such as V4. We used the model of object recognition in cortex presented by Riesenhuber and Poggio (1999), where more complex shape tuning in higher layers is the result of combining afferent inputs tuned to simpler features, and compared the tuning properties of model units in intermediate layers to those of V4 neurons from the literature. In particular, we investigated the issue of shape representation in visual area V1 and V4 using oriented bars and various types of gratings (polar, hyperbolic, and Cartesian), as used in several physiology experiments. Our computational model was able to reproduce several physiological findings, such as the broadening distribution of the orientation bandwidths and the emergence of a bias toward non-Cartesian stimuli. Interestingly, the simulation results suggest that some V4 neurons receive input from afferents with spatially separated receptive fields, leading to experimentally testable predictions. However, the simulations also show that the stimulus set of Cartesian and non-Cartesian gratings is not sufficiently complex to probe shape tuning in higher areas, necessitating the use of more complex stimulus sets.

Rotation Invariant Object Recognition from One Training Example

Local descriptors are increasingly used for the task of object recognition because of their perceived robustness with respect to occlusions and to global geometrical deformations. Such a descriptor--based on a set of oriented Gaussian derivative filters-- is used in our recognition system. We report here an evaluation of several techniques for orientation estimation to achieve rotation invariance of the descriptor. We also describe feature selection based on a single training image. Virtual images are generated by rotating and rescaling the image and robust features are selected. The results confirm robust performance in cluttered scenes, in the presence of partial occlusions, and when the object is embedded in different backgrounds.

Perceptual cues for orientation in a two finger haptic grasp task

Single point interaction haptic devices do not provide the natural grasp and manipulations found in the real world, as afforded by multi-fingered haptics. The present study investigates a two-fingered grasp manipulation involving rotation with and without force feedback. There were three visual cue conditions: monocular, binocular and projective lighting. Performance metrics of time and positional accuracy were assessed. The results indicate that adding haptics to an object manipulation task increases the positional accuracy but slightly increases the overall time taken.

Constraining the orbital orientation of eta Carinae from H Paschen lines

During the past decade, several observational and theoretical works have provided evidence of the binary nature of eta Carinae. Nevertheless, there is still no direct determination of the orbital parameters, and the different current models give contradictory results. The orbit is, in general, assumed to coincide with the Homunculus equator although the observations are not conclusive. Among all systems, eta Car has the advantage that it is possible to observe both the direct emission of line transitions in the central source and its reflection by the Homunculus, which is dependent on the orbital inclination. In this work, we studied the orbital phase-dependent hydrogen Paschen spectra reflected by the south-east lobe of the Homunculus to constrain the orbital parameters of eta Car and determine its inclination with respect to the Homunculus axis. Assuming that the emission excess originates in the wind-wind shock region, we were able to model the latitude dependence of the spectral line profiles. For the first time, we were able to estimate the orbital inclination of eta Car with respect to the observer and to the Homunculus axis. The best fit occurs for an orbital inclination to the line of sight of i similar to 60 degrees +/- 10 degrees, and i* similar to 35 degrees +/- 10 degrees with respect to the Homunculus axis, indicating that the angular momenta of the central object and the orbit are not aligned. We were also able to fix the phase angle of conjunction as similar to -40 degrees, showing that periastron passage occurs shortly after conjunction.

DETERMINATION of THE INDIRECT ORIENTATION of ORBITAL PUSHBROOM IMAGES USING CONTROL STRAIGHT LINES

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Automatic absolute orientation of scanned aerial photographs

Image orientation is a basic problem in Digital Photogrammetry. While interior and relative orientations were succesfully automated, the same can not be said about absolute orientation. This process can be automated by using an approach based on relational matching and a heuristic that uses the analytical relation between straight features in the object space and its homologous in the image space. A build-in self-diagnosis is also used in this method, that is based on the implementation of data snooping statistic test in the process of spatial resection, using the Iterated Extended Kalman Filtering (IEKF). The aim of this paper is to present the basic principles of the proposed approach and results based on real data.

A photogrammetric method for single image orientation and measurement

The aim of this paper is to present a photogrammetric method for determining the dimensions of flat surfaces, such as billboards, based on a single digital image. A mathematical model was adapted to generate linear equations for vertical and horizontal lines in the object space. These lines are identified and measured in the image and the rotation matrix is computed using an indirect method. The distance between the camera and the surface is measured using a lasermeter, providing the coordinates of the camera perspective center. Eccentricity of the lasermeter center related to the camera perspective center is modeled by three translations, which are computed using a calibration procedure. Some experiments were performed to test the proposed method and the achieved results are within a relative error of about 1 percent in areas and distances in the object space. This accuracy fulfills the requirements of the intended applications. © 2005 American Society for Photogrammetry and Remote Sensing.

A semi-automatic method for indirect orientation of aerial images using ground control lines extracted from airborne laser scanner data

This paper presents a method for indirect orientation of aerial images using ground control lines extracted from airborne Laser system (ALS) data. This data integration strategy has shown good potential in the automation of photogrammetric tasks, including the indirect orientation of images. The most important characteristic of the proposed approach is that the exterior orientation parameters (EOP) of a single or multiple images can be automatically computed with a space resection procedure from data derived from different sensors. The suggested method works as follows. Firstly, the straight lines are automatically extracted in the digital aerial image (s) and in the intensity image derived from an ALS data-set (S). Then, correspondence between s and S is automatically determined. A line-based coplanarity model that establishes the relationship between straight lines in the object and in the image space is used to estimate the EOP with the iterated extended Kalman filtering (IEKF). Implementation and testing of the method have employed data from different sensors. Experiments were conducted to assess the proposed method and the results obtained showed that the estimation of the EOP is function of ALS positional accuracy.