21,935 research outputs found
Priority search technique for MPEG-4 motion estimation of arbitrarily shaped video object
2001-2002 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe
Momentum Control with Hierarchical Inverse Dynamics on a Torque-Controlled Humanoid
Hierarchical inverse dynamics based on cascades of quadratic programs have
been proposed for the control of legged robots. They have important benefits
but to the best of our knowledge have never been implemented on a torque
controlled humanoid where model inaccuracies, sensor noise and real-time
computation requirements can be problematic. Using a reformulation of existing
algorithms, we propose a simplification of the problem that allows to achieve
real-time control. Momentum-based control is integrated in the task hierarchy
and a LQR design approach is used to compute the desired associated closed-loop
behavior and improve performance. Extensive experiments on various balancing
and tracking tasks show very robust performance in the face of unknown
disturbances, even when the humanoid is standing on one foot. Our results
demonstrate that hierarchical inverse dynamics together with momentum control
can be efficiently used for feedback control under real robot conditions.Comment: 21 pages, 11 figures, 4 tables in Autonomous Robots (2015
MPEG-4 Software Video Encoding
A Thesis submitted in fulfillment of the requirements of the degree of doctor of Philosophy in the University of LondonThis thesis presents a software model that allows a parallel decomposition of the
MPEG-4 video encoder onto shared memory architectures, in order to reduce its
total video encoding time.
Since a video sequence consists of video objects each of which is likely to have
different encoding requirements, the model incorporates a scheduler which
(a) always selects the most appropriate video object for encoding and,
(b) employs a mechanism for dynamically allocating video objects allocation onto
the system processors, based on video object size information.
Further spatial video object parallelism is exploited by applying the single program
multiple data (SPMD) paradigm within the different modules of the MPEG-4
video encoder. Due to the fact that not all macroblocks have the same processing
requirements, the model also introduces a data partition scheme that generates tiles
with identical processing requirements. Since, macroblock data dependencies
preclude data parallelism at the shape encoder the model also introduces a new
mechanism that allows parallelism using a circular pipeline macroblock technique
The encoding time depends partly on an encoderâs computational complexity. This
thesis also addresses the problem of the motion estimation, as its complexity has a
significant impact on the encoderâs complexity. In particular, two fast motion
estimation algorithms have been developed for the model which reduce the
computational complexity significantly. The thesis includes experimental results on a four processor shared memory
platform, Origin200
A Low Power Architectural Framework for Automated Surveillance System with Low Bit Rate Transmission
Abstract The changed security scenario of the modern time has necessitated increased and sophisticated vigilance of the countries' borders. The technological challenges involved in accomplishing such feat of automated security system are many and require research at the components-and-algorithms as well as the architectural levels. This paper proposes an architectural framework for automated video surveillance comprising a network of sensors and closed circuit television cameras as well as proposing algorithmic/component research of software and hardware for the core functioning of the framework, such as: communication protocols, object detection, data-integration, object identification, object tracking, video compression, threat identification, and alarm generation. In this paper, we are addressing some general topological and routing features that would be adopted in our system. There are two types of data with regard to data communication â video stream and object detection. The network is broken down into several disjoint, almost equal zones. A zone have one or more one cluster. A zone manager is chosen among the cluster heads depending on their relative residual energies. There are several levels of control that could be implemented with this arrangement with localized decision made, to get distributed effect at all levels. A cell tracks each target in its zone. If the target moves out of the range of a cell, the cell manager will send the target description to estimated next cell. The next cell starts tracking the target. If the estimated cell is wrongly chosen, corrections will be made by the cluster heads to get the new target-tracking. We also propose bitrate reduction algorithms to accommodate the limited bandwidth. One of the main feature of this paper is introducing a Low-Power Low-Bit rate video compression algorithm to accommodate the low power requirements at sensor nodes, and the low bit rate requirement for the communication protocol. We proposed two algorithms the ALBR and LPHSME. ALBR is addressing low bit rate required for sensors network with limited bandwidth which achieves a reduction in Average number of bits per Iframe by approximately 60% in case of low motion video sequences and 53% in case of fast motion video sequences . LPHSME addresses low power requirements of multi sensor network that has limited power batteries. The performance of the proposed LPHSME algorithm versus full search and three step search indicates a reduction in motion estimation time by approximately 89% in case of low motion video sequences (e.g., Claire ) and 84% in case of fast motion video sequences. The reduced complexity of LPHSME results in low power requirements
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