A new e-shopping system using high performance Custom Computers. Yuk Ying
Chung, Yong Sun, PengHao Wang, XiaoMing Chen. School of Information ...
A new e-shopping system using high performance Custom Computers Yuk Ying Chung, Yong Sun, PengHao Wang, XiaoMing Chen School of Information Technologies, The University of Sydney, NSW 2006, Australia Abstract:
The current e-shopping systems only provide the pictures and price lists of all items for shoppers to browse and make the purchase request through Internet. This kind of shopping is very boring and the shoppers can not enjoy it. In this project, we propose a new concept of e-shopping that provides customers the perception of physical shopping. The e-shop will be constructed directly from and co-existed with a physical shop. Customers can navigate in a physical shop rather than only browse pictures and price lists. Customers will perceive the presence of other shoppers around and have the feeling of inside the physical shop without physically presence in a shop. This new eshopping system can allow multiple customers to navigate within the physical shop, to select goods and make their requests to buy them.
Introduction Most shoppers enjoy shopping because they enjoy the “crowded” effect of having other fellow shoppers around, touching and watching the goods, seeing which goods are most popular and other shoppers crowd in to buy. Some may enjoy pushing the trolley around in supermarkets even though they may not have any particular items to buy initially. If we can provide the atmosphere of a physical shop to the shoppers, this can boost the visit rate of shopping site and the purchase rate of merchandises. Although some current e-shops have already had three-dimensional virtual space for customers to navigate with, the atmosphere is not the same as physical shop. In this project, we propose a new concept of eshopping that provides customers the perception of physical shopping. The e-shop will be constructed directly from and co-existed with a physical shop. Customers can navigate in a physical shop rather than only browse pictures and price lists. In order to make this e-shopping system have a real-time interactive performance, we will implement it by reconfigurable architectures using Field Programmable Gate Arrays (FPGAs). These architectures will be evaluated using simulations and proving some theoretical results on the maximal throughput of
the systems. The video processing algorithms are very simple in implementation by software. However the speed is not fast enough to be processed in real time. Custom computer based on reconfigurable logic allows the advantages of specialised hardware support for algorithm while retaining the reprogrammability and rapid prototyping advantages of software implementations.
Design of the system Cameras will be used in this e-shopping system. Therefore, what are happening in the physical shop can be taken and transmitted to the eshoppers. This can offer the e-shoppers with the atmosphere of a physical shop. To implement this system, we first need to install a dense net of cameras inside the shop to cover almost every possible viewpoint in the shop for the e-shoppers to choose. The e-shoppers can choose any particular camera and view particular items. The e-movement can be done by the change of cameras assigned to them. Our proposed new e-shopping system consists of a physical shop equipped with cameras everywhere. Each e-shopper would have a current viewpoint from a particular camera and is allowed to switch his view from one camera to another neighbouring camera. This e-shop can be able to determine the intended change of viewpoints, from a wide-angle between different shelves and close-up view of a particular merchandise. Figure 1 shows that important feature of the e-shop. This system will allow the users to switch the view if they click or drag the mouse left and right, the system will show them the views from the neighbouring cameras. For example, the viewpoint will be switched from the current camera to the camera on the left if the shopper click or drag the mouse on the left of the screen. The system will provide the gradual change of viewpoints to the e-shoppers. The change of viewpoints will be implemented by the block matching motion estimation algorithms.
Proceedings of the 28th Annual International Computer Software and Applications Conference (COMPSAC’04) 0730-3157/04 $20.00 © 2004 IEEE
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Figure 1: Wide angles between two different shelves and four different close up views of four different goods. If we use the general purpose workstation or PC to implement this e-shopping system server, it cannot perform quickly enough to provide real time interaction with the shoppers as this system will require much computational power. The use of VLSI/ASIC to design the circuitry for specific algorithm will have more effective result but this specific hardware architecture is limited to process specific algorithms. Therefore we will implement our new e-shopping system by an alternative machine architecture that provides both software versatility and hardware performance. The reconfigurable custom computer [FCCM] can be configured as a wide class of specific hardware systems. Hardware and software can be merged together into a single programmable resource in custom computers . Motion Estimation: The basic technique used for motion estimation is by searching [FGW97]. All searches seek to find the best matching macroblock-sized set of pixels in the predicted frame as compared to those in the current frame. This predicted frame can be either a subsequent frame or a previous frame. Census Transform: The direct FPGA implementation of the Block Matching Motion Estimation (BMME) would be very expensive in terms of logic gates and Look Up Table (LUT) RAM usage. An alternative is to use non -parametic similarity measure [ZW94] such as census transform. Consider the small image patch I : We can represent the local intensity pattern I by a corresponding window where each bit encodes the intensity of the corresponding neighbourhood pixel relative to the centre pixel : This bit pattern can then be represented as a bit string, in this case, the binary number 000101101, known as the census value. The census value thus encodes the local intensity
7 10 9 I = 5 6 4 3 8 2
pattern and is immune to intensity offsets or gradual gradients. Proposed system architecture: This implementation has three main stages: (1) Compute the census value of two different blocks in two different frames. (2) Compare two census values using the exclusive OR operation and count the number of ze ro bits (which indicate matching results). The sum of the number of matching bits over a larger window provides the similarity measure. (3) Find the maximum of the array of computed similarity measure, the index is the motion vector output. 0 0 0 I = 1 x 0 1 0 1
If the census transform is applied to the block matching motion estimation, it can save the FPGAs’ logic gates in terms of ROM storage and arithmetic computations. Hence it can speed up by approximate 5 times. Block diagram of Custom Computer System Previous Frame Input
Census Transform
Current Frame Input
Census Transform
Block Matching Motion Estimation
Motion Vector Output
Biblog raphy [FCCM] Proceedings of IEEE Workshop on FPGA’s for Custom Computing Machines, Napa Valley California, April, 993, 1994, 1995, 1996, 1997, 1998,1999,2000,2001. [FGW97] B.Furht, J.Greenberg, R.Westwater, “Motion Estimation algorithms for Video Compression”, Kluwer Academic Publishers, 1997. [ZW94] R.Zabih and J.Woodfill, “Nonparametric local transforms for computing visual correspondence”, Proc. 3rd European Conference Computer Vision, Stockholm, May 1994.
Proceedings of the 28th Annual International Computer Software and Applications Conference (COMPSAC’04) 0730-3157/04 $20.00 © 2004 IEEE
