Analisi di video con visione binoculare

Nel TCR - Termina container Ravenna, è importante che nel momento di scarico del container sul camion non siano presenti persone nell’area. In questo elaborato si descrive la realizzazione e il funzionamento di un sistema di allarme automatico, in grado di rilevare persone ed eventualmente interrompere la procedura di scarico del container. Tale sistema si basa sulla tecnica della object segmentation tramite rimozione dello sfondo, a cui viene affiancata una classificazione e rimozione delle eventuali ombre con un metodo cromatico. Inoltre viene identificata la possibile testa di una persona e avendo a disposizione due telecamere, si mette in atto una visione binoculare per calcolarne l’altezza. Infine, viene presa in considerazione anche la dinamica del sistema, per cui la classificazione di una persona si può basare sulla grandezza, altezza e velocità dell’oggetto individuato.

Robotic grasping: State of the art and modular real-world implementation

Robotic Grasping is an important research topic in robotics since for robots to attain more general-purpose utility, grasping is a necessary skill, but very challenging to master. In general the robots may use their perception abilities like an image from a camera to identify grasps for a given object usually unknown. A grasp describes how a robotic end-effector need to be positioned to securely grab an object and successfully lift it without lost it, at the moment state of the arts solutions are still far behind humans. In the last 5–10 years, deep learning methods take the scene to overcome classical problem like the arduous and time-consuming approach to form a task-specific algorithm analytically. In this thesis are present the progress and the approaches in the robotic grasping field and the potential of the deep learning methods in robotic grasping. Based on that, an implementation of a Convolutional Neural Network (CNN) as a starting point for generation of a grasp pose from camera view has been implemented inside a ROS environment. The developed technologies have been integrated into a pick-and-place application for a Panda robot from Franka Emika. The application includes various features related to object detection and selection. Additionally, the features have been kept as generic as possible to allow for easy replacement or removal if needed, without losing time for improvement or new testing.

3D Visual Data-Driven Spatiotemporal Deformations for Non-Rigid Object Grasping Using Robot Hands

Sensing techniques are important for solving problems of uncertainty inherent to intelligent grasping tasks. The main goal here is to present a visual sensing system based on range imaging technology for robot manipulation of non-rigid objects. Our proposal provides a suitable visual perception system of complex grasping tasks to support a robot controller when other sensor systems, such as tactile and force, are not able to obtain useful data relevant to the grasping manipulation task. In particular, a new visual approach based on RGBD data was implemented to help a robot controller carry out intelligent manipulation tasks with flexible objects. The proposed method supervises the interaction between the grasped object and the robot hand in order to avoid poor contact between the fingertips and an object when there is neither force nor pressure data. This new approach is also used to measure changes to the shape of an object’s surfaces and so allows us to find deformations caused by inappropriate pressure being applied by the hand’s fingers. Test was carried out for grasping tasks involving several flexible household objects with a multi-fingered robot hand working in real time. Our approach generates pulses from the deformation detection method and sends an event message to the robot controller when surface deformation is detected. In comparison with other methods, the obtained results reveal that our visual pipeline does not use deformations models of objects and materials, as well as the approach works well both planar and 3D household objects in real time. In addition, our method does not depend on the pose of the robot hand because the location of the reference system is computed from a recognition process of a pattern located place at the robot forearm. The presented experiments demonstrate that the proposed method accomplishes a good monitoring of grasping task with several objects and different grasping configurations in indoor environments.

Capacity limits for the detection of changing visual features

Capacity limits in visual attention have traditionally been studied using static arrays of elements from which an observer must detect a target defined by a certain visual feature or combination of features. In the current study we use this visual search paradigm, with accuracy as the dependent variable, to examine attentional capacity limits for different visual features undergoing change over time. In Experiment 1, detectability of a single changing target was measured under conditions where the type of change (size, speed, colour), the magnitude of change, the set size and homogeneity of the unchanging distractors were all systematically varied. Psychometric function slopes were calculated for different experimental conditions and ‘change thresholds’extracted from these slopes were used in Experiment 2, in which multiple supra-threshold changes were made, simultaneously, either to a single or to two or three different stimulus elements. These experiments give an objective psychometric paradigm for measuring changes in visual features over time. Results favour object-based accounts of visual attention, and show consistent differences in the allocation of attentional capacity to different perceptual dimensions.

Chemical evolution of the Galactic bulge as traced by microlensed dwarf and subgiant stars III. Detection of lithium in the metal-poor bulge dwarf MOA-2010-BLG-285S

Context. To study the evolution of Li in the Galaxy it is necessary to observe dwarf or subgiant stars. These are the only long-lived stars whose present-day atmospheric chemical composition reflects their natal Li abundances according to standard models of stellar evolution. Although Li has been extensively studied in the Galactic disk and halo, to date there has only been one uncertain detection of Li in an unevolved bulge star. Aims. Our aim with this study is to provide the first clear detection of Li in the Galactic bulge, based on an analysis of a dwarf star that has largely retained its initial Li abundance. Methods. We performed a detailed elemental abundance analysis of the bulge dwarf star MOA-2010-BLG-285S using a high-resolution and high signal-to-noise spectrum obtained with the UVES spectrograph at the VLT when the object was optically magnified during a gravitational microlensing event (visual magnification A similar to 550 during observation). The Li abundance was determined through synthetic line profile fitting of the (7)Li resonance doublet line at 670.8 nm. The results have been corrected for departures from LTE. Results. MOA-2010-BLG-285S is, at [Fe/H] = -1.23, the most metal-poor dwarf star detected so far in the Galactic bulge. Its old age (12.5 Gyr) and enhanced [alpha/Fe] ratios agree well with stars in the thick disk at similar metallicities. This star represents the first unambiguous detection of Li in a metal-poor dwarf star in the Galactic bulge. We find an NLTE corrected Li abundance of log epsilon(Li) = 2.16, which is consistent with values derived for Galactic disk and halo dwarf stars at similar metallicities and temperatures. Conclusions. Our results show that there are no signs of Li enrichment or production in the Galactic bulge during its earliest phases. Observations of Li in other galaxies (omega Cen) and other components of the Galaxy suggest further that the Spite plateau is universal.

Land use / land cover change detection: an object oriented approach, Münster, Germany

Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies

Automatic visual detection of human behavior: a review from 2000 to 2014

Due to advances in information technology (e.g., digital video cameras, ubiquitous sensors), the automatic detection of human behaviors from video is a very recent research topic. In this paper, we perform a systematic and recent literature review on this topic, from 2000 to 2014, covering a selection of 193 papers that were searched from six major scientific publishers. The selected papers were classified into three main subjects: detection techniques, datasets and applications. The detection techniques were divided into four categories (initialization, tracking, pose estimation and recognition). The list of datasets includes eight examples (e.g., Hollywood action). Finally, several application areas were identified, including human detection, abnormal activity detection, action recognition, player modeling and pedestrian detection. Our analysis provides a road map to guide future research for designing automatic visual human behavior detection systems.

Instrumentation and software for the VERITAS Project and the detection of TeV Gamma-Ray Emission from the BL Lacertae Object 1ES1959+650

Transmission of Cherenkov light through the atmosphere is strongly influenced by the optical clarity of the atmosphere and the prevailing weather conditions. The performance of telescopes measuring this light is therefore dependent on atmospheric effects. This thesis presents software and hardware developed to implement a prototype sky monitoring system for use on the proposed next-generation gamma-ray telescope array, VERITAS. The system, consisting of a CCD camera and a far-infrared pyrometer, was successfully installed and tested on the ten metre atmospheric Cherenkov imaging telescope operated by the VERITAS Collaboration at the F.L. Whipple Observatory in Arizona. The thesis also presents the results of observations of the BL Lacertae object, 1ES1959+650, made with the Whipple ten metre telescope. The observations provide evidence for TeV gamma-ray emission from the BL Lacertae object, 1ES1959+650, at a level of more than 15 standard deviations above background. This represents the first unequivocal detection of this object at TeV energies, making it only the third extragalactic source seen at such levels of significance in this energy range. The flux variability of the source on a number of timescales is also investigated.

Selective integration of auditory-visual looming cues by humans.

An object's motion relative to an observer can confer ethologically meaningful information. Approaching or looming stimuli can signal threats/collisions to be avoided or prey to be confronted, whereas receding stimuli can signal successful escape or failed pursuit. Using movement detection and subjective ratings, we investigated the multisensory integration of looming and receding auditory and visual information by humans. While prior research has demonstrated a perceptual bias for unisensory and more recently multisensory looming stimuli, none has investigated whether there is integration of looming signals between modalities. Our findings reveal selective integration of multisensory looming stimuli. Performance was significantly enhanced for looming stimuli over all other multisensory conditions. Contrasts with static multisensory conditions indicate that only multisensory looming stimuli resulted in facilitation beyond that induced by the sheer presence of auditory-visual stimuli. Controlling for variation in physical energy replicated the advantage for multisensory looming stimuli. Finally, only looming stimuli exhibited a negative linear relationship between enhancement indices for detection speed and for subjective ratings. Maximal detection speed was attained when motion perception was already robust under unisensory conditions. The preferential integration of multisensory looming stimuli highlights that complex ethologically salient stimuli likely require synergistic cooperation between existing principles of multisensory integration. A new conceptualization of the neurophysiologic mechanisms mediating real-world multisensory perceptions and action is therefore supported.

Accurate memory for object location by individuals with intellectual disability: Absolute spatial tagging instead of configural processing?

Using head-mounted eye tracker material, we assessed spatial recognition abilities (e.g., reaction to object permutation, removal or replacement with a new object) in participants with intellectual disabilities. The "Intellectual Disabilities (ID)" group (n=40) obtained a score totalling a 93.7% success rate, whereas the "Normal Control" group (n=40) scored 55.6% and took longer to fix their attention on the displaced object. The participants with an intellectual disability thus had a more accurate perception of spatial changes than controls. Interestingly, the ID participants were more reactive to object displacement than to removal of the object. In the specific test of novelty detection, however, the scores were similar, the two groups approaching 100% detection. Analysis of the strategies expressed by the ID group revealed that they engaged in more systematic object checking and were more sensitive than the control group to changes in the structure of the environment. Indeed, during the familiarisation phase, the "ID" group explored the collection of objects more slowly, and fixed their gaze for a longer time upon a significantly lower number of fixation points during visual sweeping.

Local Features in Image and Video Processing - Object Class Matching and Video Shot Detection

The usage of digital content, such as video clips and images, has increased dramatically during the last decade. Local image features have been applied increasingly in various image and video retrieval applications. This thesis evaluates local features and applies them to image and video processing tasks. The results of the study show that 1) the performance of different local feature detector and descriptor methods vary significantly in object class matching, 2) local features can be applied in image alignment with superior results against the state-of-the-art, 3) the local feature based shot boundary detection method produces promising results, and 4) the local feature based hierarchical video summarization method shows promising new new research direction. In conclusion, this thesis presents the local features as a powerful tool in many applications and the imminent future work should concentrate on improving the quality of the local features.

"What" and "Where" in the intraparietal sulcus : an fMRI study of object identity and location in visual short-term memory

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal

Translation Invariance in Object Recognition, and Its Relation to Other Visual Transformations

Human object recognition is generally considered to tolerate changes of the stimulus position in the visual field. A number of recent studies, however, have cast doubt on the completeness of translation invariance. In a new series of experiments we tried to investigate whether positional specificity of short-term memory is a general property of visual perception. We tested same/different discrimination of computer graphics models that were displayed at the same or at different locations of the visual field, and found complete translation invariance, regardless of the similarity of the animals and irrespective of direction and size of the displacement (Exp. 1 and 2). Decisions were strongly biased towards same decisions if stimuli appeared at a constant location, while after translation subjects displayed a tendency towards different decisions. Even if the spatial order of animal limbs was randomized ("scrambled animals"), no deteriorating effect of shifts in the field of view could be detected (Exp. 3). However, if the influence of single features was reduced (Exp. 4 and 5) small but significant effects of translation could be obtained. Under conditions that do not reveal an influence of translation, rotation in depth strongly interferes with recognition (Exp. 6). Changes of stimulus size did not reduce performance (Exp. 7). Tolerance to these object transformations seems to rely on different brain mechanisms, with translation and scale invariance being achieved in principle, while rotation invariance is not.

Robust real-time tracking for visual surveillance

This paper describes a real-time multi-camera surveillance system that can be applied to a range of application domains. This integrated system is designed to observe crowded scenes and has mechanisms to improve tracking of objects that are in close proximity. The four component modules described in this paper are (i) motion detection using a layered background model, (ii) object tracking based on local appearance, (iii) hierarchical object recognition, and (iv) fused multisensor object tracking using multiple features and geometric constraints. This integrated approach to complex scene tracking is validated against a number of representative real-world scenarios to show that robust, real-time analysis can be performed. Copyright (C) 2007 Hindawi Publishing Corporation. All rights reserved.

Motion detection and motion verbs: language affects low-level visual perception

Recent theories propose that semantic representation and sensorimotor processing have a common substrate via simulation. We tested the prediction that comprehension interacts with perception, using a standard psychophysics methodology.While passively listening to verbs that referred to upward or downward motion, and to control verbs that did not refer to motion, 20 subjects performed a motion-detection task, indicating whether or not they saw motion in visual stimuli containing threshold levels of coherent vertical motion. A signal detection analysis revealed that when verbs were directionally incongruent with the motion signal, perceptual sensitivity was impaired. Word comprehension also affected decision criteria and reaction times, but in different ways. The results are discussed with reference to existing explanations of embodied processing and the potential of psychophysical methods for assessing interactions between language and perception.