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Wireless video applications for Industrial Internet Of Things (IoT) are expanding into a multitude of new services. In the example of cloud processing for visual object detection, a camera is connected to the cloud via a local server and a data network, allowing the processing load to be handled in a distributed manner. This service model heavy taxes the data network with potentially unneeded traffic,...
As a key part of failure analysis function in semiconductor foundry industry, TEM micro-topography becomes more and more important while semiconductor devices' critical dimensions get smaller and smaller. And the FIB/TEM sample preparation technique takes the first priority to achieve high quality TEM pictures. Normally FIB operators have to avoid sample defects such as sample bending, poor thickness...
In context of Industry 4.0 Augmented Reality (AR) is frequently mentioned as the upcoming interface technology for human-machine communication and collaboration. Many prototypes have already arisen in both the consumer market and in the industrial sector. According to numerous experts it will take only few years until AR will reach the maturity level to be deployed in productive applications. Especially...
In order to obtain real-time accurate detection of smoke in the panoramic area, a visual-based smoke early warning system is designed. A 180-degree holographic and high speed camera is equipped as the video capture part of the system, and the video acquisition and target lock functions are implemented. The intelligent recognition function is separated into three steps. Firstly, the suspected smoke...
Convolutional Neural Networks (CNNs) are responsible for major breakthroughs in object recognition in still images. This work presents an end to end very deep architecture with small convolutional kernel size, small convolutional strides and very deep network architecture for person re-identification in video streams. To achieve such system several good practices for the training were tested, namely:...
Recent advances in technology and rapid growth of consumer electronics have made tremendous amount of multimedia information available to the general population. Browsing through large collections of consumer videos and manually creating summaries can be tedious. Automatic summarization techniques will give the user an easy way to look up important content of a collection of media and to browse media...
There are many applications employing image processing and/or control algorithms. Video surveillance, visual inspection of manufactured goods are among the examples. Self — driven cars are today one of the hottest topic. Using powerful image processing, control and learning technologies, self-driven vehicles appears to be just around the corner. Another possible application are robots in charge of...
This paper deals with the dependence of Constant Rate Factor (CRF) on the bitrate for most commercial used compression standards H.264 and H.265. The measurements were done for eight different video sequences with high resolutions (HD, Full HD, Ultra HD) depending on content. The results indicated biggest differences in the coding efficiency in CRF range from 10 to 20 and from 40 to 51 by both mentioned...
Computer vision based technologies have seen widespread adoption over the recent years. This use is not limited to the rapid adoption of facial recognition technology but extends to facial expression recognition, scene recognition and more. These developments raise privacy concerns and call for novel solutions to ensure adequate user awareness, and ideally, control over the resulting collection and...
Vehicle re-identification (re-id) plays an important role in the automatic analysis of the drastically increasing urban surveillance videos. Similar to the other image retrieval problems, vehicle re-id suffers from the difficulties caused by various poses of vehicles, diversified illuminations, and complicated environments. Triplet-wise training of convolutional neural network (CNN) has been studied...
We propose a two-stream network for face tampering detection. We train GoogLeNet to detect tampering artifacts in a face classification stream, and train a patch based triplet network to leverage features capturing local noise residuals and camera characteristics as a second stream. In addition, we use two different online face swaping applications to create a new dataset that consists of 2010 tampered...
This paper compares two allocation methods of bandwidth for each video traffic in multi-view video and audio transmission over bandwidth guaranteed IP networks. The methods are a main viewpoint prioritized allocation method and an equally allocation method. We assume simultaneous video transmission of multiple viewpoints. When bandwidth is insufficient for simultaneously transmitted multiple video...
Swarms of drones are increasingly being requested to carry out missions that cannot be completed by single drones. Particularly in the field of civil security, strong needs emerge in terms of surveillance and observation of hostile, distant or extended areas. Currently, existing solutions do not meet this demand, as they are generally based on too heavy infrastructures or over-processing, without...
This paper presents a single-chip trinocular disparity estimation processor, capable of computing in real-time up to 2048×1080 resolution depth maps at 32fps with up to 256-pixel disparity range using two/three CMOS camera sensors. The most important feature of the presented design is that the chip is based on a trinocular adaptive window matching process that requires very limited on-chip memory,...
Motivated by streaming multi-view video coding, we consider the problem of blockwise streaming compression of a pair of correlated sources, which we term streaming Slepian-Wolf coding. We study the moderate deviations regime in which the rate pairs of a sequence of codes converges, along a straight line, to various points on the boundary of the Slepian-Wolf region at a speed slower than the inverse...
A network of drone cameras can be deployed to cover live events, such as high-action sports game played on a large field, but managing networked drone cameras in real-time is challenging. Distributed approaches yield suboptimal solutions from lack of coordination but coordination with a centralized controller incurs round-trip latencies of several hundreds of milliseconds over a wireless channel....
We consider the problem of next frame prediction from video input. A recurrent convolutional neural network is trained to predict depth from monocular video input, which, along with the current video image and the camera trajectory, can then be used to compute the next frame. Unlike prior next-frame prediction approaches, we take advantage of the scene geometry and use the predicted depth for generating...
Situational awareness involves the timely acquisition of knowledge about real-world events, distillation of those events into higher-level conceptual constructs, and their synthesis into a coherent context-sensitive view. We explore how convergent trends in video sensing, crowd sourcing and edge computing can be harnessed to create a shared real-time information system for situational awareness in...
A wireless camera network can provide situation awareness information (e.g., humans in distress) in scenarios such as disaster recovery. If such camera sensors are battery operated, sending raw video feeds back to a central controller can be expensive in terms of energy consumption. Further, if all cameras were to use the optimal processing algorithm for object decision, they may also expend unnecessary...
360-degree video is on the cusp of going mainstream. Such videos have a large size (4-5⌉ the size of a regular one). Since each viewer has to wear Head-Mounted Display (HMD), screen sharing is impossible when a group is watching the same content. Multiple parallel video-streams will be required to serve a group of viewers along the last mile (think of a family or a group of friends watching...
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