Real-Time Visual SLAM Using Pre - Existing Floor Lines as Landmarks and a Single Camera

SANTANA, André M.; SANTIAGO, Gutemberg S.; MEDEIROS, Adelardo A. D. Real-Time Visual SLAM Using Pre-Existing Floor Lines as Landmarks and a Single Camera. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, 2008, Juiz de Fora, MG. Anais... Juiz de Fora: CBA, 2008.

Analisi sperimentale e progettazione di cinematismi atti alla movimentazione di devices protesici all’interno di una camera di deposizione pvd

analisi sperimentale e progettazione di cinematismi atti alla movimentazione di devices protesici all’interno di una camera di deposizione pvd. descrizione delle tecniche di deposizione PVD attualmente esistenti. deduzione e progetto ex novo, con l'ausilio di Autodesk Inventor (CAD 3D), di movimentazioni per particolari devices medici dalla geometria complessa all'interno di una speciale camera di deposizione.

Feature-based camera pose estimation

The estimating of the relative orientation and position of a camera is one of the integral topics in the field of computer vision. The accuracy of a certain Finnish technology company’s traffic sign inventory and localization process can be improved by utilizing the aforementioned concept. The company’s localization process uses video data produced by a vehicle installed camera. The accuracy of estimated traffic sign locations depends on the relative orientation between the camera and the vehicle. This thesis proposes a computer vision based software solution which can estimate a camera’s orientation relative to the movement direction of the vehicle by utilizing video data. The task was solved by using feature-based methods and open source software. When using simulated data sets, the camera orientation estimates had an absolute error of 0.31 degrees on average. The software solution can be integrated to be a part of the traffic sign localization pipeline of the company in question.

Pose estimation of a humanoid robot using images from a mobile external camera

NOGUEIRA, Marcelo B. ; MEDEIROS, Adelardo A. D. ; ALSINA, Pablo J. Pose Estimation of a Humanoid Robot Using Images from an Mobile Extern Camera. In: IFAC WORKSHOP ON MULTIVEHICLE SYSTEMS, 2006, Salvador, BA. Anais... Salvador: MVS 2006, 2006.

Real-Time Visual SLAM Using Pre - Existing Floor Lines as Landmarks and a Single Camera

SANTANA, André M.; SANTIAGO, Gutemberg S.; MEDEIROS, Adelardo A. D. Real-Time Visual SLAM Using Pre-Existing Floor Lines as Landmarks and a Single Camera. In: CONGRESSO BRASILEIRO DE AUTOMÁTICA, 2008, Juiz de Fora, MG. Anais... Juiz de Fora: CBA, 2008.

Focus giurisprudenziale. Sentenza 8/09/2015, Grande Camera della Corte di Lussemburgo, c.d. caso Taricco

Con sentenza Sez. 3 Num. 2210 Anno 2016 - Relatore: Scarcella Alessio - Data Udienza: 17/09/2015, la Cassazione, in una ipotesi di cd. “grave frode IVA”, ha disapplicato la specifica norma di cui all'ultima parte del terzo comma dell'art. 160 ed al secondo comma dell'art. 161 cod. pen. a seguito della sentenza della Corte di Giustizia U.E. dell'8 settembre 2015 (Grande Sezione), Taricco, causa C-105/14.

Texture-Detail Preservation Measurement in Camera Phones: An Updated Approach

Recent advances in mobile phone cameras have poised them to take over compact hand-held cameras as the consumer’s preferred camera option. Along with advances in the number of pixels, motion blur removal, face-tracking, and noise reduction algorithms have significant roles in the internal processing of the devices. An undesired effect of severe noise reduction is the loss of texture (i.e. low-contrast fine details) of the original scene. Current established methods for resolution measurement fail to accurately portray the texture loss incurred in a camera system. The development of an accurate objective method to identify the texture preservation or texture reproduction capability of a camera device is important in this regard. The ‘Dead Leaves’ target has been used extensively as a method to measure the modulation transfer function (MTF) of cameras that employ highly non-linear noise-reduction methods. This stochastic model consists of a series of overlapping circles with radii r distributed as r−3, and having uniformly distributed gray level, which gives an accurate model of occlusion in a natural setting and hence mimics a natural scene. This target can be used to model the texture transfer through a camera system when a natural scene is captured. In the first part of our study we identify various factors that affect the MTF measured using the ‘Dead Leaves’ chart. These include variations in illumination, distance, exposure time and ISO sensitivity among others. We discuss the main differences of this method with the existing resolution measurement techniques and identify the advantages. In the second part of this study, we propose an improvement to the current texture MTF measurement algorithm. High frequency residual noise in the processed image contains the same frequency content as fine texture detail, and is sometimes reported as such, thereby leading to inaccurate results. A wavelet thresholding based denoising technique is utilized for modeling the noise present in the final captured image. This updated noise model is then used for calculating an accurate texture MTF. We present comparative results for both algorithms under various image capture conditions.

Tracking people in 3D using position, size and shape

This paper presents a prototype tracking system for tracking people in enclosed indoor environments where there is a high rate of occlusions. The system uses a stereo camera for acquisition, and is capable of disambiguating occlusions using a combination of depth map analysis, a two step ellipse fitting people detection process, the use of motion models and Kalman filters and a novel fit metric, based on computationally simple object statistics. Testing shows that our fit metric outperforms commonly used position based metrics and histogram based metrics, resulting in more accurate tracking of people.

Mapping of indoor environments by robots using low-cost vision sensors

For robots to operate in human environments they must be able to make their own maps because it is unrealistic to expect a user to enter a map into the robot’s memory; existing floorplans are often incorrect; and human environments tend to change. Traditionally robots have used sonar, infra-red or laser range finders to perform the mapping task. Digital cameras have become very cheap in recent years and they have opened up new possibilities as a sensor for robot perception. Any robot that must interact with humans can reasonably be expected to have a camera for tasks such as face recognition, so it makes sense to also use the camera for navigation. Cameras have advantages over other sensors such as colour information (not available with any other sensor), better immunity to noise (compared to sonar), and not being restricted to operating in a plane (like laser range finders). However, there are disadvantages too, with the principal one being the effect of perspective. This research investigated ways to use a single colour camera as a range sensor to guide an autonomous robot and allow it to build a map of its environment, a process referred to as Simultaneous Localization and Mapping (SLAM). An experimental system was built using a robot controlled via a wireless network connection. Using the on-board camera as the only sensor, the robot successfully explored and mapped indoor office environments. The quality of the resulting maps is comparable to those that have been reported in the literature for sonar or infra-red sensors. Although the maps are not as accurate as ones created with a laser range finder, the solution using a camera is significantly cheaper and is more appropriate for toys and early domestic robots.

Documentary practice in a participatory culture

Debates concerning the veracity, ethics and politics of the documentary form circle endlessly around the function of those who participate in it, and the meaning attributed to their participation. Great significance is attached to the way that documentary filmmakers do or do not participate in the world they seek to represent, just as great significance is attached to those subjects whose participation extends beyond playing the part of eyewitness or expert, such that they become part of the very filmmaking process itself. This Ph.D. explores the interface between documentary practice and participatory culture by looking at how their practices, discursive fields and histories intersect, but also by looking at how participating in one might mean participating in the other. In short, the research is an examination of participatory culture through the lens of documentary practice and documentary criticism. In the process, however, this examination of participatory culture will in turn shed light on documentary thinking, especially the meaning and function of ‘the participant’ in contemporary documentary practice. A number of ways of conceiving of participation in documentary practice are discussed in this research, but one of the ideas that gives purpose to that investigation is the notion that the participant in contemporary documentary practice is someone who belongs to a participatory culture in particular. Not only does this mean that those subjects who play a part in a documentary are already informed by their engagement with a range of everyday media practices before the documentary apparatus arrives, the audience for such films are similarly informed and engaged. This audience have their own expectations about how they should be addressed by media producers in general, a fact that feeds back into their expectations about participatory approaches to documentary practice too. It is the ambition of this research to get closer to understanding the relationship between participants in the audience, in documentary and ancillary media texts, as well as behind the camera, and to think about how these relationships constitute a context for the production and reception of documentary films, but also how this context might provide a model for thinking about participatory culture itself. One way that documentary practice and participatory culture converge in this research is in the kind of participatory documentary that I call the ‘Camera Movie’, a narrow mode of documentary filmmaking that appeals directly to contemporary audiences’ desires for innovation and participation, something that is achieved in this case by giving documentary subjects control of the camera. If there is a certain inevitability about this research having to contend with the notion of the ‘participatory documentary’, the ‘participatory camera’ also emerges strongly in this context, especially as a conduit between producer and consumer. Making up the creative component of this research are two documentaries about the reality television event Band In A Bubble, and participatory media practices more broadly. The single-screen film, Hubbub , gives form to the collective intelligence and polyphonous voice of contemporary audiences who must be addressed and solicited in increasingly innovative ways. One More Like That is a split-screen, DVD-Video with alternate audio channels selected by a user who thereby chooses who listens and who speaks in the ongoing conversation between media producers and media consumers. It should be clear from the description above that my own practice does not extend to highly interactive, multi-authored or web-enabled practices, nor the distributed practices one might associate with social media and online collaboration. Mine is fundamentally a single authored, documentary video practice that seeks to analyse and represent participatory culture on screen, and for this reason the Ph.D. refrains from a sustained discussion of the kinds of collaborative practices listed above. This is not to say that such practices don’t also represent an important intersection of documentary practice and participatory culture, they simply represent a different point of intersection. Being practice-led, this research takes its procedural cues from the nature of the practice itself, and sketches parameters that are most enabling of the idea that the practice sets the terms of its own investigation.

Love at first sight : Sanja Pahoki

I am a landscape architect, a non-photographer, and in reviewing this exhibition, it seems that in a critical discourse on photography the nature of the view and its relation to the observer (presumably the camera) is inevitably a key focus of creative inquiry, in an epistemological sense. In conducting such a review, of 'self-portraits' by 'female photographers' in relation to 'the landscape', one cannot help but ask what priority this critique should allocate to each of these conceptual agendas, quite apart from the simple formal quality of the individual pieces themselves. Analytically, each could form the axes of a matrix that might allow for a number of quite different permutations and therefore differently conclusive commentaries on the others: the view vs landscape; the view vs sexuality; the self-portrait vs the landscape picture. All of these would be productive in their own right and each is alluded to in the works themselves and in the narrative of the catalogue. Considering this range of possible permutations, this show is certainly rich and this richness sits well with the relative formal saturation of the images themselves.

Adaptive unsupervised learning of human actions

Automatic detection of suspicious activities in CCTV camera feeds is crucial to the success of video surveillance systems. Such a capability can help transform the dumb CCTV cameras into smart surveillance tools for fighting crime and terror. Learning and classification of basic human actions is a precursor to detecting suspicious activities. Most of the current approaches rely on a non-realistic assumption that a complete dataset of normal human actions is available. This paper presents a different approach to deal with the problem of understanding human actions in video when no prior information is available. This is achieved by working with an incomplete dataset of basic actions which are continuously updated. Initially, all video segments are represented by Bags-Of-Words (BOW) method using only Term Frequency-Inverse Document Frequency (TF-IDF) features. Then, a data-stream clustering algorithm is applied for updating the system's knowledge from the incoming video feeds. Finally, all the actions are classified into different sets. Experiments and comparisons are conducted on the well known Weizmann and KTH datasets to show the efficacy of the proposed approach.