Nowadays, there is high commercial demand for product replacement which places the products virtually in Key Opinion Leader’s (KOL’s) social media videos. However, one of the challenges of placing the products virtually is the KOL segmentation. Since KOLs often hold products in front of them, it requires the segmentation to segment not only humans but also different products. This paper introduces the state-of-the-art deep learning method, namely RSUDISNet, for KOL segmentation. The proposed technique integrates two deep Convolutional Neural Network (CNN) technologies. One is the Matting Objective Decomposition Network (MODNet), which segments KOLs well but not the products blocking the KOLs. The other one is the two-level nested U-structure network (U2Net) based on the salient object detection method to segment the objects well, but not the KOL. The key technique of the proposed research is to employ the feature of the U2Net to embed the MODNet to overcome the problem of KOL segmentation. Since both MODNet and U2Net are lightweights, the combined network can be used for real-time scenarios. After that, the Intermediate Supervision (IS) training strategy is utilized to overcome the overfitting. The experimental results show that our proposed method outperforms the MODNet and U2Net.

There has been an increasing interest in deploying wireless mesh networks (WMNs) for communication and video surveillance purposes thanks to its low cost and ease of deployment. It is well known that a major drawback of WMN is multihop bandwidth degradation, which is primarily caused by contention and radio interference. The use of mesh nodes with multiple radios and channels has been regarded as a straightforward solution to the problem in the research community. However, we demonstrate in this paper through real-world experiments that such an approach cannot resolve the multihop TCP throughput degradation problem in IEEE 802.11n mesh networks. With extensive experimentation, we verify that the degradation is principally caused by the increase in TCP Round-Trip Time (RTT) when the number of hops increases. TCP throughput is fundamentally limited inversely by the RTT. We find that the multihop TCP throughput (up to five hops) when using 802.11n is no better than when using 802.11a, despite the much higher data rate 802.11n. We attempt to use multiple parallel TCP connections as a remedy to the problem, and it turns out that the wireless bandwidth can be fully utilized with a sufficient number of parallel streams. In general, our results give a key message that TCP tuning (e.g., setting the correct TCP buffers and use of parallel streams) is of paramount importance in high-bandwidth multihop wireless mesh networks that employ the latest wireless standards. These tuning techniques have to be implemented into commercial products to fully leverage the ever advancing wireless technologies to support the growing demand of multihop communications in wireless mesh networks.

A main distinguishing feature of a wireless network compared with a wired network is its broadcast nature, in which the signal transmitted by a node may reach several other nodes, and a node may receive signals from several other nodes simultaneously. Rather than a blessing, this feature is treated more as an interference-inducing nuisance in most wireless networks today (e.g., IEEE 802.11). The goal of this paper is to show how the concept of network coding can be applied at the physical layer to turn the broadcast property into a capacity-boosting advantage in wireless ad hoc networks. Specifically, we propose a physical-layer network coding (PNC) scheme to coordinate transmissions among nodes. In contrast to "straightforward" network coding which performs coding arithmetic on digital bit streams after they have been received, PNC makes use of the additive nature of simultaneously arriving electromagnetic (EM) waves for equivalent coding operation. PNC can yield higher capacity than straight-forward network coding when applied to wireless networks. We believe this is a first paper that ventures into EM-wave-based network coding at the physical layer and demonstrates its potential for boosting network capacity. PNC opens up a whole new research area because of its implications and new design requirements for the physical, MAC, and network layers of ad hoc wireless stations. The resolution of the many outstanding but interesting issues in PNC may lead to a revolutionary new paradigm for wireless ad hoc networking.

The concept of care-of-address (CoA) is a major cause of excessive handoff delay in Mobile IPv6 for real time multimedia traffic. Many schemes eliminate the use of CoA at the micro-mobility scale, but leave the macro-mobility unsolved. This paper proposes a novel alternative IPv6 mobility scheme based on universal addressing - Cellular Universal IP (CUIP) - for real-time traffic in wireless access networks. In CUIP, a mobile node is addressed with a universal IP address regardless of its location, making CoA and tunneling unnecessary in micromobility and even macromobility handoffs. CUIP manages roaming and handoff differently - whereas explicit signaling is used for roaming, a handoff-on-the-fly route-update scheme is used during handoff to embed signaling information into the outgoing data packets to minimize handoff delay. We prove analytically that, on average, fewer than three routers need to be updated per handoff. As a result, CUIP incurs an expected network layer handoff delay on the order of milliseconds only. In addition, the support of QoS is possible. A simple security scheme is also proposed to enable mutual authentication at the network layer.