scholarly journals Development and implementation of interactive 3D video environment on run-time reconfigurable FPGA platform

2021 ◽  
Author(s):  
Sergiy Zhelnakov

Video data processing tasks are traditionally performed either through software-based systems when various algorithms must be applied to the data and when time issue is not critical, DSPs -- when certain time constraints are set but when the set of tasks is limited, or ASICs -- when the highest performance is required, the set of tasks is fixed and highly optimized, the data stream doesn't change, and the number of data streams is limited. For a real-time system which must operate on multiple data streams which also can change in time and on which various data processing algorithms must be applied neither of the mentioned approaches can be used. Timing requirements and power limitation does not allow utilization of sequential CPU. ASIC becomes too big to accomodate multiple processing circuits for each algorithm and associated modes. Only Run-Time Reconfigurable (RTR) FPGA approach allows implementation of such a system. The thesis presents a real-time stereo vision system with elements of synthesis of interactive 3-D virtual objects designed and implemented on the FPGA-based reconfigurable platform. FPGA chip integrates a hybrid architecture system with multi-mode and mutli-stream processing ability for critical time tasks and with embedded microprocessor(s) for computing complex algorithms for 3-D objects synthesis for which timing requirements are not so strict. An approach for the formal presentation and processing of the 3-D virtual objects and their transformation is also analyzed and presented in this paper. Architecture synthesis and optimization for a hybrid system are also considered. The experimental results proved the effectiveness of proposed approach: the FPGA-based system-on-chip provides stereo visualization in different modes (actual image and edge detection image), with synthesized 3-D controls (pressed and released buttons).

2021 ◽  
Author(s):  
Sergiy Zhelnakov

Video data processing tasks are traditionally performed either through software-based systems when various algorithms must be applied to the data and when time issue is not critical, DSPs -- when certain time constraints are set but when the set of tasks is limited, or ASICs -- when the highest performance is required, the set of tasks is fixed and highly optimized, the data stream doesn't change, and the number of data streams is limited. For a real-time system which must operate on multiple data streams which also can change in time and on which various data processing algorithms must be applied neither of the mentioned approaches can be used. Timing requirements and power limitation does not allow utilization of sequential CPU. ASIC becomes too big to accomodate multiple processing circuits for each algorithm and associated modes. Only Run-Time Reconfigurable (RTR) FPGA approach allows implementation of such a system. The thesis presents a real-time stereo vision system with elements of synthesis of interactive 3-D virtual objects designed and implemented on the FPGA-based reconfigurable platform. FPGA chip integrates a hybrid architecture system with multi-mode and mutli-stream processing ability for critical time tasks and with embedded microprocessor(s) for computing complex algorithms for 3-D objects synthesis for which timing requirements are not so strict. An approach for the formal presentation and processing of the 3-D virtual objects and their transformation is also analyzed and presented in this paper. Architecture synthesis and optimization for a hybrid system are also considered. The experimental results proved the effectiveness of proposed approach: the FPGA-based system-on-chip provides stereo visualization in different modes (actual image and edge detection image), with synthesized 3-D controls (pressed and released buttons).


2017 ◽  
Vol 14 (1) ◽  
pp. 64-68 ◽  
Author(s):  
Peng Shi ◽  
Li Li

The functions of the network analysis system include detection and analysis of network data stream. According to the results of the network analysis, we monitor the network accident and avoid the security risks. This can improve the network performance and increase the network availability. As the data flow in the network is constantly produced, the biggest characteristic of network analysis system is that it is a real-time system. Because of the high requirements of the network data analysis and network fault processing, the system requires very high processing efficiency of the real time data of network. Stream computing is a technique specifically for processing real-time data streams. Its idea is that the value of the data is reduced with the lapse of time, so as long as the data appearing, it must be processed as soon as possible. So we use the technology of stream computing to design network analysis system to meet the needs of real-time capability. Moreover, the stream computing framework has been widely welcomed in the field because of its good expansibility, ease of use and flexibility. In this paper, firstly, we introduce the characteristics of the data processing based on stream computing and the traditional data processing separately. We point out their difference and introduce the technique of stream computing. Then, we introduce the architecture of network analysis system designed base on the technique of stream computing. The architecture includes two main components that are logic processing layer and communication layer. We describe the characteristics of each component and functional characteristics in detail, and we introduce the system load balancing algorithm. Finally, by experiments, we verify the effectiveness of the system’s characteristics of dynamic expansion and load balancing.


Author(s):  
Jia Xu

Methods for handling process underruns and overruns when scheduling a set of real-time processes increase both system utilization and robustness in the presence of inaccurate estimates of the worst-case computations of real-time processes. In this paper, we present a method that efficiently re-computes latest start times for real time processes during run-time in the event that a real-time process is preempted or has completed (or overrun). The method effectively identifies which process latest start times will be affected by the preemption or completion of a process. Hence the method is able to effectively reduce real-time system overhead by selectively re-computing latest start times for the specific processes whose latest start times are changed by a process preemption or completion, as opposed to indiscriminately re-computing latest start times for all the processes.


Author(s):  
Semion Kizhner ◽  
Karin B. Blank ◽  
Jennifer A. Sichler ◽  
Umeshkumar D. Patel ◽  
Jacqueline Le Moigne ◽  
...  

A smart camera performs real-time analysis to recognize scenic elements. Smart cameras are useful in a variety of scenarios: surveillance, medicine, etc. We have built a real-time system for recognizing gestures. Our smart camera uses novel algorithms to recognize gestures based on low-level analysis of body parts as well as hidden Markov models for the moves that comprise the gestures. These algorithms run on a Tri media processor. Our system cans recognize gestures at the rate of 20 frames /second. The camera can also fuse the results of multiple cameras. The smart camera – a whole vision system contained in one neat housing can be used anywhere, in any industry where image processing can be applied. Companies no longer need a cabinet in which to keep all their computing equipment: the computer is housed within the smart camera. In the pharmaceutical industry and in clean rooms – when not even dust is allowed – this can be a big advantage. A single square meter of space can be comparatively very expensive if there is no need for a component rack or cabinet, simply a smart camera, and then this could save a lot of money.


Author(s):  
Parimala N.

A data stream is a real-time continuous sequence that may be comprised of data or events. Data stream processing is different from static data processing which resides in a database. The data stream data is seen only once. It is too voluminous to store statically. A small portion of data called a window is considered at a time for querying, computing aggregates, etc. In this chapter, the authors explain the different types of window movement over incoming data. A query on a stream is repeatedly executed on the new data created by the movement of the window. SQL extensions to handle continuous queries is addressed in this chapter. Streams that contain transactional data as well as those that contain events are considered.


Author(s):  
Alexey Khakhulin ◽  
Igor Orlovsky ◽  
Yuriy Sheynin ◽  
Ilya Korobkov ◽  
Valentin Olenev ◽  
...  

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