Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

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 encoder’s computational complexity. This thesis also addresses the problem of the motion estimation, as its complexity has a significant impact on the encoder’s 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 Novel Hybrid Approach for Fast Block Based Motion Estimation

The current work presents a novel hybrid approach for motion estimation of various video sequences with a purpose to speed up the entire process without affecting the accuracy. The method integrates the dynamic Zero motion pre-judgment (ZMP) technique with Initial search centers (ISC) along with half way search termination and Small diamond search pattern. Calculation of the initial search centers has been shifted after the process of zero motion pre-judgment unlike most the previous approaches so that the search centers for stationary blocks need not be identified. Proper identification of ISC dismisses the need to use any fast block matching algorithm (BMA) to find the motion vectors (MV), rather a fixed search pattern such as small diamond search pattern is sufficient to use. Half way search termination has also been incorporated into the algorithm which helps in deciding whether the predicted ISC is the actual MV or not which further reduced the number of computations. Simulation results of the complete hybrid approach have been compared to other standard methods in the field. The method presented in the manuscript ensures better video quality with fewer computations

Motion estimation with chessboard pattern prediction strategy

Due to high correlations among the adjacent blocks, several algorithms utilize movement information of spatially and temporally correlated neighboring blocks to adapt their search patterns to that information. In this paper, this information is used to define a dynamic search pattern. Each frame is divided into two sets, black and white blocks, like a chessboard pattern and a different search pattern, is defined for each set. The advantage of this definition is that the number of spatially neighboring blocks is increased for each current block and it leads to a better prediction for each block. Simulation results show that the proposed algorithm is closer to the Full-Search algorithm in terms of quality metrics such as PSNR than the other state-of-the-art algorithms while at the same time the average number of search points is less.info:eu-repo/semantics/publishedVersio

Online, interactive user guidance for high-dimensional, constrained motion planning

We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches that try to speed up planning by incorporating experiences or demonstrations ahead of planning, we suggest to seek user guidance only when the planner identifies that it ceases to make significant progress towards the goal. Guidance is provided in the form of an intermediate configuration $\hat{q}$, which is used to bias the planner to go through $\hat{q}$. We demonstrate our approach for the case where the planning algorithm is Multi-Heuristic A* (MHA*) and the robot is a 34-DOF humanoid. We show that our approach allows to compute highly-constrained paths with little domain knowledge. Without our approach, solving such problems requires carefully-crafting domain-dependent heuristics

Online, interactive user guidance for high-dimensional, constrained motion planning

We consider the problem of planning a collision-free path for a high-dimensional robot. Specifically, we suggest a planning framework where a motion-planning algorithm can obtain guidance from a user. In contrast to existing approaches that try to speed up planning by incorporating experiences or demonstrations ahead of planning, we suggest to seek user guidance only when the planner identifies that it ceases to make significant progress towards the goal. Guidance is provided in the form of an intermediate configuration $\hat{q}$, which is used to bias the planner to go through $\hat{q}$. We demonstrate our approach for the case where the planning algorithm is Multi-Heuristic A* (MHA*) and the robot is a 34-DOF humanoid. We show that our approach allows to compute highly-constrained paths with little domain knowledge. Without our approach, solving such problems requires carefully-crafting domain-dependent heuristics