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Plenary Speakers PDF Print E-mail

SPEAKER 1 --> 3D Video: Some Challenging Topics

Prof. Hsueh-Ming Hang

Electrical and Computer Engineering College 
National Chiao-Tung University, Taiwan



3D films have a history of several decades, but only recently 3D video consumer products are gradually becoming popular. The focus of next-generation 3D research is on the so-called virtual-viewpoint (or free-viewpoint) video system. It is also an on-going standardization item in the international ITU/MPEG Standards. Typically, a densely arranged camera array is used to acquire input images and a number of virtual view pictures are synthesized at the receiver using the depth-image based rendering (DIBR) technique. Three essential components are needed for building a virtual-view system: depth estimation, data compression, and view synthesis. An interesting application of virtual-view system is 3D scene composition. It is an extension of the traditional chroma key technique but it now tries to merge two sets of 3D vide scenes into one consistent 3D scene. Another issue is depth map acquisition. Recent devices such as Microsoft Kinect offers an inexpensive hardware solution to this problem. However, its depth map quality needs to be improved. We will give a quick overview of these challenging topics and summarize our studies on these subjects.


SPEAKER 2 --> Emerging Smart Sensors: From Technologies to Applications

Prof. Sergey Y. Yurish

International Frequency Sensor Association (IFSA)



The Global Smart Sensors Market is expected to reach at $9.22 billion in 2018, growing at a CAGR of 11.53 % over the period 2014 to 2020 . MarketsandMarkets reports that the smart sensor market is expected to reach $10.46 billion in 2020 from $650 million in 2012 at a CAGR of 36.25 % from 2013 to 2020. Smart sensor consist of a sensing element, analog‐to‐digital converter and a bus interface in a package having features such as signal/data‐processing capabilities, logic function, communications and so on [2]. The major benefits offered by a smart sensor are high reliability, cost effectiveness and scalability. The major challenge associated with the smart sensor is the pre‐defined embedded functions have to be provided during designing of smart sensors.

The level of smart sensor integration is heavily driven by technology scaling. The main reason for scaling is increased system performance at reduced manufacturing cost. Below the 100 nm technology, the design of analog and mixed‐signal circuits becomes perceptibly more difficult. This is particularly true for low supply voltage near 1 V or below. The result is not only an increased design effort, long development time, high risk, cost, and the need for very high volumes, but also growing power consumption. There are many reasons that analog doesn’t scale as readily. However, digital circuits scale very well with scaling standard CMOS technologies. So, the promised trend is the transition from traditional analog informative parameters such as voltage and current to the quasi‐digital informative parameters of sensors outputs, for example, frequency, period, duty‐cycle, PWM, phase shift, pulse number. etc. It means the use of frequency (period)‐to‐digital converters instead of tradition analog‐to‐digital converters, and implements as many system components as possible in the digital form. It lets get over technological limitations at scaling and gives a great opportunity to significantly improve the metrological performance of various sensor systems. Clear, the design of high performance frequency (period)‐to‐digital converters is not a trivial task of low cost microcontroller use. It needs novel, advanced methods for frequency‐time measurements in a wide frequency range with high accuracy and non‐redundant conversion time.

The presentation deals with advanced, novel smart sensor systems design and its applications in smartphones, tablets and IoT. Coming technological limitations, and challenges will be outlined, and new technological trends will be described in details. The integration of the USTI‐MOB into sensor systems has the potential to greatly simplify the design of the system and contribute to further increasing of system level integration, flexibility and functionality.




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