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Human-machine interactive systems show increasing demand for analysing fast moving objects in high-frame-rate videos. Robust foreground detection, which is able to reduce large amount of redundant background data from high-frame-rate video, becomes the essence to achieve ultra-high-speed human-machine interactions. This paper proposes a local spatial propagation based background model generation, a local linear illumination correction based background model update, and a regional central coordinates and edge keypoints constrained foreground region reselection. The three proposals make up a robust and hardware-friendly foreground detection method. Experimental results prove that the proposed hardware-friendly algorithm achieves high accuracy and robustness on various kinds of challenging cases. Meanwhile, the hardware implementation utilizes little hardware resources and achieves realtime processing of high-frame-rate (784 frame/second) video with the delay less than 1 ms/frame in image processing core. In addition, a practical system is implemented by combing a PC, a high-speed camera and a field programmable gate array (FPGA) for realworld applications. This work will significatively promote the development and application of high-speed human machine interaction. A demo of the proposed vision system working at 784 FPS is available at https://wcms.waseda.jp/em/5f84f75136a6. Note to Practitioners—This paper was motivated by the problem of high-frame-rate video contains large amount of redundant background pixels which makes ultra-high-speed human-machine interactions inaccessible. Existing approaches are mainly focused on designing complex background models, but processing speed, which is the most important issue for ultra-high-speed human-machine interactions, has received relatively little attention. This paper suggests a robust and hardware-friendly foreground detection algorithm which has been implemented as a hardware system by using an FPGA, a high-frame-rate camera, and a PC. We show that the hardware implementation utilizes less hardware resources and achieves real-time processing speed of 784 FPS with the delay less than 1 ms/frame in the image processing core. This work is a pioneering attempt of ultra-high-speed foreground detection, which will significatively speed up the wide applications of ultra-high-speed human machine interactions. [ABSTRACT FROM AUTHOR]

Preventive and reactive maintenance require the collection of an ever-increasing amount of information from industrial plants and other complex systems such as those based on robotized cells, a need that can be fulfilled by means of a suitable event notification mechanism. At the same time, timing and delivery reliability requirements in those scenarios are typically less demanding than those in other cases, thus enabling the adoption of best-effort notification approaches. This paper presents, evaluates, and compares some of those approaches, based on either standard Controller Area Network (CAN) messaging or a recently proposed protocol extension called CAN with eXtensible in-frame Reply (CAN XR). In the second case, the combined use of Bloom filters is also envisaged to increase flexibility. Results show that the latter approaches are advantageous in a range of event generation rates and network topologies of practical relevance. [ABSTRACT FROM AUTHOR]

This article presents our work proposing in-network caching in IP-based networks by adding a content identifier into a newly defined IPv6 extension header, where the new architecture is named CAIP. CAIP abandons the complicated name-based forwarding table in ICN, and instead integrates IP routing lookup with cache index lookup, which is compatible with the IP network and also inherits the proven advantages of ICN. Cache index exchanging and cooperative caching are implemented between one-hop CAIP enabled neighboring routers, which is simple but efficient. Moreover, for per-chunk caching, as an extension, bitmap is introduced to merge multiple request packets into one. Performance analysis shows that CAIP gains significant performance improvement in terms of access delay and traffic load. [ABSTRACT FROM PUBLISHER]

Controller area network (CAN) has been the de facto standard in the automotive industry for the past two decades. Recently, CAN with flexible data-rate (CAN FD) has been standardized, which achieves noticeably higher throughput. Further improvements are still possible for CAN, by exploiting its peculiar physical layer to carry out distributed operations among network nodes, implemented as atomic transactions mapped on quasi-conventional frame exchanges. In this paper, a proposal is made for an extension to the CAN protocol, termed CAN with eXtensible in-frame Reply (CAN XR), which enables upper protocol layers to define new custom services devoted to, e.g., network management, application-specific functions, and high-efficiency data transfer. The key point is that CAN XR retains full backward compatibility with CAN, therefore, there is no need to change the protocol specification once again. [ABSTRACT FROM PUBLISHER]

The bit stuffing mechanism adopted in controller area networks leads to unwanted jitter on frame reception times, which worsens timing accuracy, even if countermeasures are adopted to avoid contentions on the bus. Several solutions have been proposed so far for dealing with stuff bits in the payload of messages, but they are not effective for the cyclic redundancy check. In this paper, a mechanism is presented that prevents the occurrence of stuff bits in the whole frame completely. It makes the duration of frame transmissions fixed and, hence, it achieves very accurate reception times. An optimized codec has been implemented to demonstrate that this approach is feasible and can be profitably adopted in low-cost networked embedded systems with demanding timing constraints. [ABSTRACT FROM PUBLISHER]