In advanced manufacturing industries, there is a need to monitor the health of tools with the aim of enhancing its lifetime. Often due to several reasons such as cost and time, many organizations are faced with the difficulty in collecting complete degradation data for monitoring the tool. As such, this makes tool wear prognostics a challenging problem in the real world. Although there have been a number of studies on tool wear prognosis, the monitoring of tool wear where the complete wear data is unavailable is still a challenge. This paper presents a framework for tool wear prognosis when the degradation data is limited. First, we present an analysis of tool wear diagnosis, in which the health of tool is classified into three categories of new tool, medium worn tool and high worn tool. Next, we present the analysis of tool wear prognosis by assuming linear and non-linear degradation curves of tool wear. Real data for tool wear is collected using five different tools used for cutting with three different degrees of flank wears, namely, new, medium and high worn. Results showed high classification and prediction accuracies in terms of the trends of prediction as well as the mean squared error.

Virtual try-on of clothes has received much attention recently due to its commercial potential. It can be used for online shopping or intelligent recommendation to narrow down the selections to a few designs and sizes. In this paper, we present a mixed reality system for 3D virtual clothes try-on that enables a user to see herself wearing virtual clothes while looking at a mirror display, without taking off her actual clothes. The user can select various virtual clothes for trying-on. The system physically simulates the selected virtual clothes on the user's body in real-time and the user can see virtual clothes fitting on the her mirror image from various angles as she moves. The major contribution of this paper is that we automatically customize an invisible (or partially visible) avatar based on the user's body size and the skin color and use it for proper clothes fitting, alignment and clothes simulation in our virtual try-on system. We present three scenarios: i) virtual clothes on the avatar, ii) virtual clothes on the user's image and iii) virtual clothes on the avatar blended with the user's face image. We have conducted a user study to evaluate the effectiveness of these three solutions from the end user's perception of quality attributes, cognitive attributes and attitude towards using. The user study shows that among these three scenarios, the second one is most preferred by the users and for 50% of them the experience they had with our system was sufficient to make the purchase decision for the outfits they virtually tried-on.

This paper proposes a new method to automatically segment and re-color the clothing in an image sequence. Background and foreground are separated using background subtraction method with a Gaussian mixture model built for the static scene. Skin and face areas are detected and removed on the segmented foreground. A 2D histogram is constructed using the remaining pixels to model the probability distribution of the clothing chromaticity, which is then applied to each frame to find accurate clothing area using back projection method. The segmented clothing area is re-colored by mapping the hue value to a new one in the HSV color space to maintain the contrast of the clothing. Experiments on the real video captured with a monocular webcam are shown to demonstrate the effectiveness of the proposed algorithm for clothing segmentation and re-coloring.

A new scheme for back-projection of weights for mean shift based object tracking is proposed. Weights are calculated based on relative counts of histogram bins for each feature used in similarity assessment. A fusion scheme is proposed to combine the back-projected weights from different features, such that the dissimilarities between the object being tracked and the background are boosted. A mechanism is proposed to calculate the overall similarity between reference and candidate windows, without actually doing the back-projection, and just by few computations based on histogram bin counts. Moreover, the reference and candidate windows do not need to have the same size. The proposed scheme shows better tracking results compared to the traditional mean shift based tracking, especially in case of fast object movement and high background clutter.

We present the design and implementation of a solenoid based haptics device, which weighs less than 100 grams, and generates a acceleration of 14-g for simulating impact events in virtual reality and games. The device is used in free air, or ungrounded, and generates the high-g impacts without being attached to a large structure. The goal is to generate a more realistic impact sensations than commonly used vibration motors. The device consists of two solenoids in push-pull configuration. A low internal resistance battery system supplies high-current pulses of more than 10 amperes. During user motions, one solenoid will magnetically holds the device in ready position, so that the other solenoid achieves maximum stroke and impact output.

Abstract We present a system for interacting with 3D objects in a 3D virtual environment. Using the notion that a typical head‐mounted display (HMD) does not cover the user's entire face, we use a fiducial marker placed on the HMD to locate the user's exposed facial skin. Using this information, a skin model is built and combined with the depth information obtained from a stereo camera. The information when used in tandem allows the position of the user's hands to be detected and tracked in real time. Once both hands are located, our system allows the user to manipulate the object with five degrees of freedom (translation inx‐,y‐, andz‐ axis with roll and yaw rotations) in virtual three‐dimensional space using a series of intuitive hand gestures. Copyright © 2009 John Wiley & Sons, Ltd.

We demonstrate a method in which gesture control is enabled through use of a stereo camera. Hard to use keyboard commands are effectively emulated using positional gestures. We describe the implementation and some results from user surveys based on user's trying the application at a public exposition. Along with outlining the implementation, we report the initial findings and show evidence as to why such a gesture interface is more effective as an interface as opposed to traditional gaming interfaces.

Global tone mapping operators (TMOs) are better in preserving the naturalness and relative illumination of the HDR scene compared to the local TMOs. However, they cannot preserve the details like the local TMOs. We propose a human visual system (HVS) based histogram method for global tone mapping, which can better preserve the details than the existing global TMOs. Our method can be incorporated to all histogram based global methods. We compare our results with traditional histogram adjustment by Ward et al. [Larson97] and photographic TMO [Reinhard2002], and in most of the cases our method is better in preserving the details of the input HDR images.

One of the long-term goals in human-computer interaction is to utilize more intuitive and natural methods such as speech and hand gestures that a user would employ for communication. In this paper, we present a robust method of hand tracking using a probability map computed from a joint probability function derived from both depth information and skin-tone information. The depth information is provided using a commercially available stereo camera, and the color information is found using calibrated and linearized color information. The work shows the effectiveness of this technique, in terms of both the quality of the results as well as the speed at which the computations may be performed. Due to the linearization of the color information and the use of stereo vision data, the technique is demonstrated to be largely invariant to illumination changes.

This paper presents a new algorithm for background subtraction that can model the background image from a sequence of images, even if there are foreground objects in each image frame. In contrast with Gaussian mixture model algorithm, in our proposed method the problem of distinguishing between background and foreground kernels becomes trivial. The key idea of our method lies in the identification of the background based on QR-decomposition method in linear algebra. R-values taken from QR-decomposition can be applied to decompose a given system to indicate the degree of the significance of the decomposed parts. We split the image into small blocks and select the background blocks with the weakest contribution, according to the assigned R-values. Simulation results show the better background detection performance with respect to some others.

The paper proposes a method of compressing floating-point images of arbitrary precision. The concept of floating point images is used frequently in such areas as high dynamic range imaging, where pixel data stored as 8 or 12-bit integers are insufficient. The compression scheme presented in the paper organizes the floating point data in a manner such that already existing compression algorithms such as JPEG or Zlib compression may be used once the data re-organization has taken place. The paper compares the result to a popular (but restrictive) form of image compression, openEXR, and shows significant gains over this format. Furthermore, the compression scheme presented is scalable to deal with floating point images of arbitrary precision.

We describe an augmented reality system for superimposing three-dimensional (3-D) live content onto two-dimensional fiducial markers in the scene. In each frame, the Euclidean transformation between the marker and the camera is estimated. The equivalent virtual view of the live model is then generated and rendered into the scene at interactive speeds. The 3-D structure of the model is calculated using a fast shape-from-silhouette algorithm based on the outputs of 15 cameras surrounding the subject. The novel view is generated by projecting rays through each pixel of the desired image and intersecting them with the 3-D structure. Pixel color is estimated by taking a weighted sum of the colors of the projections of this 3-D point in nearby real camera images. Using this system, we capture live human models and present them via the augmented reality interface at a remote location. We can generate 384/spl times/288 pixel images of the models at 25 fps, with a latency of <100 ms. The result gives the strong impression that the model is a real 3-D part of the scene.

In this paper we describe two Augmented Reality (AR) applications for children using mobile phones as the user interface. We make use of standard mobile phones readily available in the consumer market without making any hardware modifications to them. The first AR application we describe is the AR Comic Book which allows children to view their favorite cartoon characters in full 3D appearing on books or magazines (or any paper). These 3D virtual characters are rendered into the actual scene captured by the mobile phone's camera. The second AR application is the AR Post-It, which combines the speed of traditional electronic messaging with the tangibility of paper based messages. The key concept of the AR Post-It system is that the messages are displayed only when the intended receiver is within the relevant spatial context. For both these applications a server is used to do the image processing tasks and the phone connects to the server using Bluetooth.

No abstract available.

We describe a real-time 3-D augmented reality video- conferencing system. With this technology, an observer sees the real world from his viewpoint, but modified so that the image of a remote collaborator is rendered into the scene. We register the image of the collaborator with the world by estimating the 3-D transformation between the camera and a fiducial marker. We describe a novel shape- from-silhouette algorithm, which generates the appropriate view of the collaborator and the associated depth map at 30 fps. When this view is superimposed upon the real world, it gives the strong impression that the collaborator is a real part of the scene. We also demonstrate interaction in virtual environments with a live fully 3-D collaborator. Finally, we consider interaction between users in the real world and collaborators in a virtual space, using a tangible AR interface.

We present a complete system for live capture of 3D content and simultaneous presentation in augmented reality. The user sees the real world from his viewpoint, but modified so that the image of a remote collaborator is rendered into the scene. Fifteen cameras surround the collaborator, and the resulting video streams are used to construct a three-dimensional model of the subject using a shape-from-silhouette algorithm. Users view a two-dimensional fiducial marker using a video-see-through augmented reality interface. The geometric relationship between the marker and head-mounted camera is calculated, and the equivalent view of the subject is computed and drawn into the scene. Our system can generate 384 /spl times/ 288 pixel images of the models at 25 fps, with a latency of < 100 ms. The result gives the strong impression that the subject is a real part of the 3D scene. We demonstrate applications of this system in 3D videoconferencing and entertainment.

This paper presents a new fuzzy-logic-control based filter with the ability to remove impulsive noise and smooth Gaussian noise, while, simultaneously, preserving edges and image details efficiently. To achieve these three image enhancement goals, we first develop filters that have excellent edge-preserving capability but do not perform well in smoothing Gaussian noise. Next, we modify the filters so that they perform all three image enhancement tasks. These filters are based on the idea that individual pixels should not be uniformly fired by each of the fuzzy rules. To demonstrate the capability of our filtering approach, it was tested on several different image enhancement problems. These experimental results demonstrate the speed, filtering quality, and image sharpening ability of the new filter.

In this paper we propose a modified iterative fuzzy logic control based filter acronymed by MIFCF for removing impulsive noise, smoothing additive & multiplicative Gaussian noise with preserving image edges and details. The high performance of our method especially in removing the multiplicative noise, in compared with those of recently proposed filters, is demonstrated by some experiments.

The paper presents an extension of our previous fuzzy logic based filtering approach whose high performance in mixed noise environments has been reported by F. Furbiz et al. (1998). This filter has also kept the general property of not letting each pixel be uniformly fired by each of the fuzzy rules. It further aims at compressing the membership functions of fuzzy linguistic terms in each iteration to enhance the filtering ability. We show through some experiments how powerful our filter is in image enhancement.

This paper presents a new filtering approach based on fuzzy-logic which has high performance in mixed noise environments. This filter is mainly based on the idea that each pixel is not allowed to be uniformly fired by each of the fuzzy rules. We perform several test experiments in order to highlight the merit of the proposed method. The results are very promising and indicating the high performance of the proposed filter in image restoration compared with those of the filters which have been previously cited in image processing literature.

This paper presents a new fuzzy-logic-control based filter with the properties of removing impulsive noise and smoothing out Gaussian noise while, simultaneously, preserving edges and image details efficiently. To reach the above three goals of the image enhancement problem, we employ the concepts of fuzzy logic control to design a filter to perform all the three tasks mentioned above. This filter is mainly based on the idea that each pixel is not allowed to be uniformly fired by each of the fuzzy rules. To demonstrate how good our filtering approach works, several different cases of image enhancement problem have been considered. From the experimental results we may list the concluding remark of the proposed filtering approach: (i) no need of floating point calculations, (ii) very fast performance of the filter compared with other proposed filters, (iii) introducing a measure to demonstrate quantitatively the quality behaviour of the filters in edge preserving, (iv) high quality of filtering especially for complex images.