ENERGY-EFFICIENT LIGHTWEIGHT ALGORITHMS FOR EMBEDDED SMART CAMERAS: DESIGN, IMPLEMENTATION AND PERFORMANCE ANALYSIS

An embedded smart camera is a stand-alone unit that not only captures images, but also includes a processor, memory and communication interface. Battery-powered, embedded smart cameras introduce many additional challenges since they have very limited resources, such as energy, processing power and memory. When camera sensors are added to an embedded system, the problem of limited resources becomes even more pronounced. Hence, computer vision algorithms running on these camera boards should be light-weight and efficient. This thesis is about designing and developing computer vision algorithms, which are aware and successfully overcome the limitations of embedded platforms (in terms of power consumption and memory usage). Particularly, we are interested in object detection and tracking methodologies and the impact of them on the performance and battery life of the CITRIC camera (embedded smart camera employed in this research). This thesis aims to prolong the life time of the Embedded Smart platform, without affecting the reliability of the system during surveillance tasks. Therefore, the reader is walked through the whole designing process, from the development and simulation, followed by the implementation and optimization, to the testing and performance analysis. The work presented in this thesis carries out not only software optimization, but also hardware-level operations during the stages of object detection and tracking. The performance of the algorithms introduced in this thesis are comparable to state-of-the-art object detection and tracking methods, such as Mixture of Gaussians, Eigen segmentation, color and coordinate tracking. Unlike the traditional methods, the newly-designed algorithms present notable reduction of the memory requirements, as well as the reduction of memory accesses per pixel. To accomplish the proposed goals, this work attempts to interconnect different levels of the embedded system architecture to make the platform more efficient in terms of energy and resource savings. Thus, the algorithms proposed are optimized at the API, middleware, and hardware levels to access the pixel information of the CMOS sensor directly. Only the required pixels are acquired in order to reduce the unnecessary communications overhead. Experimental results show that when exploiting the architecture capabilities of an embedded platform, 41.24% decrease in energy consumption, and 107.2% increase in battery-life can be accomplished. Compared to traditional object detection and tracking methods, the proposed work provides an additional 8 hours of continuous processing on 4 AA batteries, increasing the lifetime of the camera to 15.5 hours

Improving Safety and Mobility at High-Speed Intersections with Innovations in Sensor Technology

A series of innovations has been made in the vehicle sensors field. Technologies such as IntelliDrive and radar-based smart sensors make it pos­sible to track each vehicle in proximity to an intersection. However, current technologies have limitations, such as lack of robustness, accuracy, or level of penetration. This paper assumes an accurate wide-area detector (WAD), which might be soon available, and highlights the potential benefits that might be derived in safety and efficiency of oper­ations at high-speed intersections from the deployment of the WAD. Two critical areas in which wide-area detection can lead to significant improvements are discussed: (a) location of crash risk on onset of yellow and (b) location of vehicles on onset of yellow. A case study was conducted at an instrumented intersection in Noblesville, Indiana, to esti­mate potential improvement from the use of an ideally operating WAD and green extension logic for signal control. Findings revealed that the replacement of the single loop detector sensor with a WAD sensor would lead to an additional 1.4 vehicles being served per lane on the cross street per unit vehicle provided with dilemma zone protection on the high ­speed approach. Results also showed that speed traps should be used only after accounting for the trade-off between safety and efficiency and the traffic control logic. When speed traps were designed with generic dilemma zone boundaries at the Noblesville site, the dilemma zone protection was provided only 57% of the time because vehicles accelerated or decelerated after passing the speed trap

Improving Safety and Mobility at High-Speed Intersections with Innovations in Sensor Technology

A series of innovations has been made in the vehicle sensors field. Technologies such as IntelliDrive and radar-based smart sensors make it pos­sible to track each vehicle in proximity to an intersection. However, current technologies have limitations, such as lack of robustness, accuracy, or level of penetration. This paper assumes an accurate wide-area detector (WAD), which might be soon available, and highlights the potential benefits that might be derived in safety and efficiency of oper­ations at high-speed intersections from the deployment of the WAD. Two critical areas in which wide-area detection can lead to significant improvements are discussed: (a) location of crash risk on onset of yellow and (b) location of vehicles on onset of yellow. A case study was conducted at an instrumented intersection in Noblesville, Indiana, to esti­mate potential improvement from the use of an ideally operating WAD and green extension logic for signal control. Findings revealed that the replacement of the single loop detector sensor with a WAD sensor would lead to an additional 1.4 vehicles being served per lane on the cross street per unit vehicle provided with dilemma zone protection on the high ­speed approach. Results also showed that speed traps should be used only after accounting for the trade-off between safety and efficiency and the traffic control logic. When speed traps were designed with generic dilemma zone boundaries at the Noblesville site, the dilemma zone protection was provided only 57% of the time because vehicles accelerated or decelerated after passing the speed trap

Power Consumption and Performance Analysis of Object Tracking and Event Detection with Wireless Embedded Smart Cameras

An embedded smart camera is a stand-alone unit that not only captures images, but also includes a processor, memory and communication interface. With battery-powered and embedded smart cameras, it has become viable to install many spatially-distributed cameras interconnected by wireless links. Not requiring to have access to electrical outlets and have wired links increase system flexibility. However, wireless and battery-powered smart-camera networks introduce many additional challenges since they have very limited resources, such as power, memory and bandwidth. The algorithms running on the camera boards should be lightweight and efficient. In addition, the frequency of communication between camera nodes, and the content of the message packets should be carefully designed, since communication consumes power. In this paper, we present a wireless embedded smart-camera system that performs peer-topeer object tracking and event detection. We analyze the power consumption and performance of this system during different parts of the algorithm execution and for different message exchanges between camera nodes. We also present a graph of the energy consumption for different tasks performed in a camera’s processor. The number of instructions are also presented. The results demonstrate the importance of the careful choice of when and what data to transfer between cameras, and also the necessity of having lightweight algorithms in these resource-constrained systems

Energy-efficient Foreground Object Detection on Embedded Smart Cameras by Hardware-level Operations

Embedded smart cameras have limited processing power, memory and energy. In this paper, we introduce two methodologies to increase the energy-efficiency and the battery-life of an embedded smart camera by hardware level operations when performing foreground object detection. We use the CITRIC platform as our embedded smart camera. We first perform down-sampling at hardware level on the micro-controller of the image sensor rather than performing software-level down-sampling at the main microprocessor of the camera board. In addition, we crop an image frame at hardware level by using the HREF and VSYNC signals at the micro-controller of the image sensor to perform foreground object detection only in the cropped search region instead of the whole image. Thus, the amount of data that is moved from the image sensor to the main memory at each frame, is greatly reduced. Thanks to reduced data transfer, better use of the memory resources and not occupying the main microprocessor with image down-sampling and cropping tasks, we obtain significant savings in energy consumption and battery-life. Experimental results show that hardware-level down-sampling and cropping, and performing detection in cropped regions provide 54.14% decrease in energy consumption, and 121.25% increase in battery-life compared to performing software-level down sampling and processing whole frames

Peering into the Dark Side: Magnesium Lines Establish a Massive Neutron Star in PSR J2215 + 5135

New millisecond pulsars (MSPs) in compact binaries provide a good opportunity to search for the most massive neutron stars. Their main-sequence companion stars are often strongly irradiated by the pulsar, displacing the effective center of light from their barycenter and making mass measurements uncertain. We present a series of optical spectroscopic and photometric observations of PSR J2215+5135, a “redback” binary MSP in a 4.14 hr orbit, and measure a drastic temperature contrast between the dark/cold (TN = 5660- + 380 260 K) and bright/hot (TD = 8080- + 280 470 K) sides of the companion star. We find that the radial velocities depend systematically on the atmospheric absorption lines used to measure them. Namely, the semi-amplitude of the radial velocity curve (RVC) of J2215 measured with magnesium triplet lines is systematically higher than that measured with hydrogen Balmer lines, by 10%. We interpret this as a consequence of strong irradiation, whereby metallic lines dominate the dark side of the companion (which moves faster) and Balmer lines trace its bright (slower) side. Further, using a physical model of an irradiated star to fit simultaneously the two-species RVCs and the three-band light curves, we find a center-of-mass velocity of K2 = 412.3 ± 5.0 km s?1 and an orbital inclination i = 63°.9- + 2.7 2.4. Our model is able to reproduce the observed fluxes and velocities without invoking irradiation by an extended source. We measure masses of M1 = 2.27- + 0.15 0.17 Me and M2 = 0.33- + 0.02 0.03 Me for the neutron star and the companion star, respectively. If confirmed, such a massive pulsar would rule out some of the proposed equations of state for the neutron star interior

Gaps and vulnerabilities in peripheral metropolises: comparative analysis between Curitiba, Brazil and San Miguel de Tucuman, Argentina

Com a consolidação de uma América Latina urbana e o avanço da metropolização, o debate sobre as implicações destes processos é imperativo na agenda urbana do continente. Assim, compreender as dinâmicas, atores e configurações espaciais das desigualdades de forma multiescalar e comparada se constitui como um importante avanço do ponto de vista teórico e metodológico. Neste sentido, o artigo busca propor, à luz dos processos de urbanização e metropolização do Brasil e da Argentina, dois indicadores para Curitiba e São Miguel de Tucumán. O primeiro, pauta-se na mensuração da oferta dos serviços de saneamento e, o segundo, nos aspectos demográficos e de educação. Por fim, espera-se contribuir metodologicamente na leitura de padrões espaciais entre cidades latino-americanas de forma comparada utilizando dados censitários.Avec la consolidation d'une Amérique latine urbaine et la promotion de la métropole, le débat sur les implications de ces processus est impératif dans le programme urbain du continent. Ainsi, la compréhension de la dynamique, les acteurs et les configurations spatiales des inégalités de forme multi-échelle et par rapport constitue une avancée importante dans un point de vue théorique et méthodologique. En ce sens, l'article tente de proposer, à la lumière des processus d'urbanisation et métropole du Brésil et l'Argentine, deux indicateurs de Curitiba et São Miguel de Tucumán. La première, est guidé pour mesurer la fourniture de services d'assainissement et la deuxième de la démographie et de l'éducation. Enfin, nous espérons contribuer lecture méthodologique des configurations spatiales entre les villes d'Amérique latine alors comparés à l'aide des données du recensement.With the consolidation of an urban Latin America and the advancement of the metropolis, the debate on the implications of these processes is imperative in the urban agenda of the continent. Thus, understanding the dynamics, actors and spatial configurations of inequalities of multiscale shape and compared constitutes is an important advance in a theoretical and methodological point of view. In this sense, the paper attempts to propose, in the light of urbanization and metropolization processes of Brazil and Argentina, two indicators for Curitiba and San Miguel de Tucuman. The first, is guided to measure the supply of sanitation services and the second in demographics and education. Finally, we hope to contribute to a methodologically reading of spatial patterns between Latin American cities using census data.Fil: Polidoro, Mauricio. Universidade Federal do Paraná; BrasilFil: Czytajlo, Natalia Paola. Universidad Nacional de Tucuman. Facultad de Arquitectura y Urbanismo. Instituto de Planeamiento y Desarrollo Urbano. Cátedra de Urbanismo I; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Casares, Marta. Universidad Nacional de Tucuman. Facultad de Arquitectura y Urbanismo. Instituto de Planeamiento y Desarrollo Urbano. Cátedra de Urbanismo I; Argentin

Energy-efficient Feedback Tracking on Embedded Smart Cameras by Hardware-level Optimization

Embedded systems have limited processing power, memory and energy. When camera sensors are added to an embedded system, the problem of limited resources becomes even more pronounced. In this paper, we introduce two methodologies to increase the energy-efficiency and battery-life of an embedded smart camera by hardware-level operations when performing object detection and tracking. The CITRIC platform is employed as our embedded smart camera. First, down-sampling is performed at hardware level on the micro-controller of the image sensor rather than performing software-level down-sampling at the main microprocessor of the camera board. In addition, instead of performing object detection and tracking on whole image, we first estimate the location of the target in the next frame, form a search region around it, then crop the next frame by using the HREF and VSYNC signals at the micro-controller of the image sensor, and perform detection and tracking only in the cropped search region. Thus, the amount of data that is moved from the image sensor to the main memory at each frame is optimized. Also, we can adaptively change the size of the cropped window during tracking depending on the object size. Reducing the amount of transferred data, better use of the memory resources, and delegating image down-sampling and cropping tasks to the micro-controller on the image sensor, result in significant decrease in energy consumption and increase in battery-life. Experimental results show that hardware-level down-sampling and cropping, and performing detection and tracking in cropped regions provide 41.24% decrease in energy consumption, and 107.2% increase in battery-life. Compared to performing software-level down-sampling and processing whole frames, proposed methodology provides an additional 8 hours of continuous processing on 4 AA batteries, increasing the lifetime of the camera to 15.5 hours