8,723 research outputs found
Investigating the Declarative and Procedural Memory Processes Underlying Acquisition of Tool-Related Knowledge and Skills
It has been proposed that the acquisition of tool-related knowledge and skills (e.g., attributes of a tool, how it is used, how it is grasped) relies on a complex set of memory processes. However, the precise memory representations of different aspects of tool knowledge are still unclear. It has also been argued that some aspects may require an interaction between the declarative and procedural memory systems. However, the nature of this interaction between both memory systems in relation to tool-related knowledge is not well understood. A series of three experiments was carried out in the current dissertation to systematically investigate the role of declarative and procedural memory in mediating complex tool knowledge and skills. In Experiment 1 participants with Parkinson’s disease (PD) showed unimpaired memory for tool attributes and tool grasping relative to controls. In addition, participants with PD showed intact motor skill learning and skilled tool use within sessions, but failed to retain proficiency of these skills after a 3-week delay. In Experiment 2, declarative encoding processes were interrupted in healthy adults by dividing attention during training. Findings showed that dividing attention during training was detrimental for subsequent memory for tool attributes as well as accurate demonstration of tool use and tool grasping. However, dividing attention did not interfere with motor skill learning. In Experiment 3, motor procedural learning among healthy adults was disrupted by limiting access to performance-based feedback during training. Results showed that recall of tool attributes and tool grasping were intact, but limited feedback was detrimental for motor skill learning and skilled tool use. Taken together, the results suggest that memory for tool attributes and tool grasping primarily relies on declarative memory which is associated with the medial temporal lobes. In contrast, findings suggest that motor skill acquisition related to complex tools is primarily supported by striatal-dependent procedural memory. Thus, these results represent a dissociation between declarative and procedural aspects of tool knowledge and skills. Findings from the current studies also provide new insights into the interaction between declarative and procedural memory. The results suggest that skilled tool use requires a cooperative interaction of both systems. The evidence also suggests that the pattern of interaction between memory systems may vary, depending on the learning context
Complexity management of H.264/AVC video compression.
The H. 264/AVC video coding standard offers significantly improved compression efficiency and flexibility compared to previous standards. However, the high computational complexity of H. 264/AVC is a problem for codecs running on low-power hand held devices and general purpose computers. This thesis presents new techniques to reduce, control and manage the computational complexity of an H. 264/AVC codec. A new complexity reduction algorithm for H. 264/AVC is developed. This algorithm predicts "skipped" macroblocks prior to motion estimation by estimating a Lagrange ratedistortion cost function. Complexity savings are achieved by not processing the macroblocks that are predicted as "skipped". The Lagrange multiplier is adaptively modelled as a function of the quantisation parameter and video sequence statistics. Simulation results show that this algorithm achieves significant complexity savings with a negligible loss in rate-distortion performance. The complexity reduction algorithm is further developed to achieve complexity-scalable control of the encoding process. The Lagrangian cost estimation is extended to incorporate computational complexity. A target level of complexity is maintained by using a feedback algorithm to update the Lagrange multiplier associated with complexity. Results indicate that scalable complexity control of the encoding process can be achieved whilst maintaining near optimal complexity-rate-distortion performance. A complexity management framework is proposed for maximising the perceptual quality of coded video in a real-time processing-power constrained environment. A real-time frame-level control algorithm and a per-frame complexity control algorithm are combined in order to manage the encoding process such that a high frame rate is maintained without significantly losing frame quality. Subjective evaluations show that the managed complexity approach results in higher perceptual quality compared to a reference encoder that drops frames in computationally constrained situations. These novel algorithms are likely to be useful in implementing real-time H. 264/AVC standard encoders in computationally constrained environments such as low-power mobile devices and general purpose computers
Content-Aware Multimedia Communications
The demands for fast, economic and reliable dissemination of multimedia
information are steadily growing within our society. While people and
economy increasingly rely on communication technologies, engineers still
struggle with their growing complexity.
Complexity in multimedia communication originates from several sources. The
most prominent is the unreliability of packet networks like the Internet.
Recent advances in scheduling and error control mechanisms for streaming
protocols have shown that the quality and robustness of multimedia delivery
can be improved significantly when protocols are aware of the content they
deliver. However, the proposed mechanisms require close cooperation between
transport systems and application layers which increases the overall system
complexity. Current approaches also require expensive metrics and focus on
special encoding formats only. A general and efficient model is missing so
far.
This thesis presents efficient and format-independent solutions to support
cross-layer coordination in system architectures. In particular, the first
contribution of this work is a generic dependency model that enables
transport layers to access content-specific properties of media streams,
such as dependencies between data units and their importance. The second
contribution is the design of a programming model for streaming
communication and its implementation as a middleware architecture. The
programming model hides the complexity of protocol stacks behind simple
programming abstractions, but exposes cross-layer control and monitoring
options to application programmers. For example, our interfaces allow
programmers to choose appropriate failure semantics at design time while
they can refine error protection and visibility of low-level errors at
run-time.
Based on some examples we show how our middleware simplifies the
integration of stream-based communication into large-scale application
architectures. An important result of this work is that despite cross-layer
cooperation, neither application nor transport protocol designers
experience an increase in complexity. Application programmers can even
reuse existing streaming protocols which effectively increases system
robustness.Der Bedarf unsere Gesellschaft nach kostengĂĽnstiger und
zuverlässiger
Kommunikation wächst stetig. Während wir uns selbst immer mehr von modernen
Kommunikationstechnologien abhängig machen, müssen die Ingenieure dieser
Technologien sowohl den Bedarf nach schneller EinfĂĽhrung neuer Produkte
befriedigen als auch die wachsende Komplexität der Systeme beherrschen.
Gerade die Ăśbertragung multimedialer Inhalte wie Video und Audiodaten ist
nicht trivial. Einer der prominentesten GrĂĽnde dafĂĽr ist die
Unzuverlässigkeit heutiger Netzwerke, wie z.B.~dem Internet. Paketverluste
und schwankende Laufzeiten können die Darstellungsqualität massiv
beeinträchtigen. Wie jüngste Entwicklungen im Bereich der
Streaming-Protokolle zeigen, sind jedoch Qualität und Robustheit der
Ăśbertragung effizient kontrollierbar, wenn Streamingprotokolle
Informationen ĂĽber den Inhalt der transportierten Daten ausnutzen.
Existierende Ansätze, die den Inhalt von Multimediadatenströmen
beschreiben, sind allerdings meist auf einzelne Kompressionsverfahren
spezialisiert und verwenden berechnungsintensive Metriken. Das reduziert
ihren praktischen Nutzen deutlich. AuĂźerdem erfordert der
Informationsaustausch eine enge Kooperation zwischen Applikationen und
Transportschichten. Da allerdings die Schnittstellen aktueller
Systemarchitekturen nicht darauf vorbereitet sind, mĂĽssen entweder die
Schnittstellen erweitert oder alternative Architekturkonzepte geschaffen
werden. Die Gefahr beider Varianten ist jedoch, dass sich die Komplexität
eines Systems dadurch weiter erhöhen kann.
Das zentrale Ziel dieser Dissertation ist es deshalb,
schichtenĂĽbergreifende Koordination bei gleichzeitiger Reduzierung der
Komplexität zu erreichen. Hier leistet die Arbeit zwei Beträge zum
aktuellen Stand der Forschung. Erstens definiert sie ein universelles
Modell zur Beschreibung von Inhaltsattributen, wie Wichtigkeiten und
Abhängigkeitsbeziehungen innerhalb eines Datenstroms. Transportschichten
können dieses Wissen zur effizienten Fehlerkontrolle verwenden. Zweitens
beschreibt die Arbeit das Noja Programmiermodell fĂĽr multimediale
Middleware. Noja definiert Abstraktionen zur Ăśbertragung und Kontrolle
multimedialer Ströme, die die Koordination von Streamingprotokollen mit
Applikationen ermöglichen. Zum Beispiel können Programmierer geeignete
Fehlersemantiken und Kommunikationstopologien auswählen und den konkreten
Fehlerschutz dann zur Laufzeit verfeinern und kontrolliere
Respiratory organ motion in interventional MRI : tracking, guiding and modeling
Respiratory organ motion is one of the major challenges in interventional MRI, particularly in interventions with therapeutic ultrasound in the abdominal region. High-intensity focused ultrasound found an application in interventional MRI for noninvasive treatments of different abnormalities. In order to guide surgical and treatment interventions, organ motion imaging and modeling is commonly required before a treatment start. Accurate tracking of organ motion during various interventional MRI procedures is prerequisite for a successful outcome and safe therapy.
In this thesis, an attempt has been made to develop approaches using focused ultrasound which could be used in future clinically for the treatment of abdominal organs, such as the liver and the kidney. Two distinct methods have been presented with its ex vivo and in vivo treatment results. In the first method, an MR-based pencil-beam navigator has been used to track organ motion and provide the motion information for acoustic focal point steering, while in the second approach a hybrid imaging using both ultrasound and magnetic resonance imaging was combined for advanced guiding capabilities.
Organ motion modeling and four-dimensional imaging of organ motion is increasingly required before the surgical interventions. However, due to the current safety limitations and hardware restrictions, the MR acquisition of a time-resolved sequence of volumetric images is not possible with high temporal and spatial resolution. A novel multislice acquisition scheme that is based on a two-dimensional navigator, instead of a commonly used pencil-beam navigator, was devised to acquire the data slices and the corresponding navigator simultaneously using a CAIPIRINHA parallel imaging method. The acquisition duration for four-dimensional dataset sampling is reduced compared to the existing approaches, while the image contrast and quality are improved as well.
Tracking respiratory organ motion is required in interventional procedures and during MR imaging of moving organs. An MR-based navigator is commonly used, however, it is usually associated with image artifacts, such as signal voids. Spectrally selective navigators can come in handy in cases where the imaging organ is surrounding with an adipose tissue, because it can provide an indirect measure of organ motion. A novel spectrally selective navigator based on a crossed-pair navigator has been developed. Experiments show the advantages of the application of this novel navigator for the volumetric imaging of the liver in vivo, where this navigator was used to gate the gradient-recalled echo sequence
Event-based Vision: A Survey
Event cameras are bio-inspired sensors that differ from conventional frame
cameras: Instead of capturing images at a fixed rate, they asynchronously
measure per-pixel brightness changes, and output a stream of events that encode
the time, location and sign of the brightness changes. Event cameras offer
attractive properties compared to traditional cameras: high temporal resolution
(in the order of microseconds), very high dynamic range (140 dB vs. 60 dB), low
power consumption, and high pixel bandwidth (on the order of kHz) resulting in
reduced motion blur. Hence, event cameras have a large potential for robotics
and computer vision in challenging scenarios for traditional cameras, such as
low-latency, high speed, and high dynamic range. However, novel methods are
required to process the unconventional output of these sensors in order to
unlock their potential. This paper provides a comprehensive overview of the
emerging field of event-based vision, with a focus on the applications and the
algorithms developed to unlock the outstanding properties of event cameras. We
present event cameras from their working principle, the actual sensors that are
available and the tasks that they have been used for, from low-level vision
(feature detection and tracking, optic flow, etc.) to high-level vision
(reconstruction, segmentation, recognition). We also discuss the techniques
developed to process events, including learning-based techniques, as well as
specialized processors for these novel sensors, such as spiking neural
networks. Additionally, we highlight the challenges that remain to be tackled
and the opportunities that lie ahead in the search for a more efficient,
bio-inspired way for machines to perceive and interact with the world
Understanding object motion encoding in the mammalian retina.
Phototransduction, transmission of visual information down the optic nerve incurs delays on the order of 50 – 100ms. This implies that the neuronal representation of a moving object should lag behind the object’s actual position. However, studies have demonstrated that the visual system compensates for neuronal delays using a predictive mechanism called phase advancing, which shifts the population response toward the leading edge of a moving object’s retinal image. To understand how this compensation is achieved in the retina, I investigated cellular and synaptic mechanisms that drive phase advancing. I used three approaches, each testing phase advancing at a different organizational level within the mouse retina. First, I studied phase advancing at the level of ganglion cell populations, using two-photon imaging of visually evoked calcium responses. I found populations of phase advancing OFF-type, ON-type, ON-OFF type, and horizontally tuned directionally selective ganglion cells. Second, I measured synaptic current responses of individual ganglion cells with patch-clamp electrophysiology, and I used a computational model to compare the observed responses to simulated responses based on the ganglion cell’s spatio-temporal receptive fields. Third, I tested whether phase advancing originates presynaptic to ganglion cells, by assessing phase advancing at the level of bipolar cell glutamate release using two-photon imaging of the glutamate biosensor iGluSnFR expressed in the inner plexiform layer. Based on the results of my experiments, I conclude that bipolar and ganglion cell receptive field structure generates phase advanced responses and acts to compensate for neuronal delays within the retina
Content-prioritised video coding for British Sign Language communication.
Video communication of British Sign Language (BSL) is important for remote interpersonal communication and for the equal provision of services for deaf people. However, the use of video telephony and video conferencing applications for BSL communication is limited by inadequate video quality. BSL is a highly structured, linguistically complete, natural language system that expresses vocabulary and grammar visually and spatially using a complex combination of facial expressions (such as eyebrow movements, eye blinks and mouth/lip shapes), hand gestures, body movements and finger-spelling that change in space and time. Accurate natural BSL communication places specific demands on visual media applications which must compress video image data for efficient transmission. Current video compression schemes apply methods to reduce statistical redundancy and perceptual irrelevance in video image data based on a general model of Human Visual System (HVS) sensitivities. This thesis presents novel video image coding methods developed to achieve the conflicting requirements for high image quality and efficient coding. Novel methods of prioritising visually important video image content for optimised video coding are developed to exploit the HVS spatial and temporal response mechanisms of BSL users (determined by Eye Movement Tracking) and the characteristics of BSL video image content. The methods implement an accurate model of HVS foveation, applied in the spatial and temporal domains, at the pre-processing stage of a current standard-based system (H.264). Comparison of the performance of the developed and standard coding systems, using methods of video quality evaluation developed for this thesis, demonstrates improved perceived quality at low bit rates. BSL users, broadcasters and service providers benefit from the perception of high quality video over a range of available transmission bandwidths. The research community benefits from a new approach to video coding optimisation and better understanding of the communication needs of deaf people
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