Pictures have become increasingly common and popular in mobile communications. However, due to the limitation of mobile devices, there is a need to develop new technologies to facilitate the browsing of large pictures on the small screen. In this paper, we propose a novel approach which is able to automate the scrolling and navigation of a large picture with a minimal amount of user interaction on mobile devices. An image attention model is employed to illustrate the information structure within an image. An optimal image browsing path is then calculated based on the image attention model to simulate the human browsing behaviors. Experimental evaluations of the proposed mechanism indicate that our approach is an effective way for viewing large images on small displays.

Foveation and stereopsis are important features on active vision systems. The former provides a wide field of view and high foveal resolution with low amounts of data, while the latter contributes to the acquisition of close range depth cues. The log-polar sampling has been proposed as an approximation to the foveated representation of the primate visual system. Although the huge amount of stereo algorithms proposed in the literature for conventional imaging geometries, very few are shown to work with foveated images sampled according to the log-polar transformation. In this paper we present a method to extract dense disparity maps in real-time from a pair of log-mapped images, with direct application to active vision systems.

Projections in a foveal space at u approximate functions with a resolution that decreases proportionally to the distance from u. Such spaces are de ned by dilating a nite family of foveal wavelets, which are not translated. Their general properties are studied and illustrated with spline functions. Orthogonal bases are constructed with foveal wavelets of compact support and high regularity. Foveal wavelet coecients give pointwise characterization of non-oscillatory singularities. An algorithm to detect singularities and choose foveal points is derived. Precise approximations of piecewise regular functions are obtained with foveal approximations centered at singularity locations. 1

Voluminous spatio-temporal data make multimedia analysis tasks extremely inefficient and lack of adaptability. We present a novel experience based sampling technique which has the ability to focus on the analysis’s task by making use of the contextual information and past experiences. Based on this, a sampling based dynamic attention model is built by sensing the experiential environment. Sensor samples are used to gather information about the current environment and attention samples are used to represent the current state of attention. In our framework, the taskattended samples are inferred from experiences and maintained by a sampling based dynamical system. The multimedia analysis task can then focus on the attention samples only. Moreover, past experiences and the current environment can be used to adaptively correct and tune the attention. As a prototypical multimedia analysis task, we tackle the face detection problem in videos. Face detection is only performed on the attended samples to achieve robust real time processing. Experimental results have been presented to demonstrate the efficacy of our technique. This experience based sampling based analysis method appears to be a promising technique for general multimedia analysis problems. The generality stems from the power of the sampling method which makes no assumptions about the form of distribution of attention which is usually multimodal in nature.

Pictures have become increasingly common and popular in mobile communications. However, due to the limitation of mobile devices, there is a need to develop new technologies to facilitate the browsing of large pictures on the small screen. In this paper, we propose a set of novel approaches which are able to aid or automate common image browsing tasks on mobile devices. All of these approaches are based on an image attention model which is employed to illustrate the information structure within an image. An efficient algorithm to generate the optimal browsing path based on the information foraging theory is presented. Experimental evaluations of the proposed mechanism indicate that our approach is an effective way for viewing large images on small displays.

Image authentication is becoming very important for certifying data integrity. A key issue in image authentication is the design of a compact signature that contains sufficient information to detect illegal tampering yet is robust under allowable manipulations. In this paper, we recognize that most permissible operations on images are global distortions like low-pass filtering and JPEG compression, whereas illegal data manipulations tend to be localized distortions. To exploit this observation, we propose an image authentication scheme where the signature is the result of an extremely low-bit-rate content-based compression. The content-based compression is guided by a space-variant weighting function whose values are higher in the more important and sensitive region. This spatially dependent weighting function determines a weighted norm that is particularly sensitive to the localized distortions induced by illegal tampering. It also gives a better compactness compared to the usual compression schemes that treat every spatial region as being equally important. In our implementation, the weighting function is a multifovea weighted function that resembles the biological foveated vision system. The foveae are salient points determined in the scale-space representation of the image. The desirable properties of multifovea weighted function in the wavelet domains fit nicely into our scheme. We have implemented our technique and tested its robustness and sensitivity for several manipulations.

Abstract: With development of biomedical and networking technology, interactive volume rendering with data transmitted via the network becomes an interesting topic. Two technical problems are data transmission and fast volume rendering. In this paper, two schemes using Wavelet foveation are proposed and implemented: the region-based and coarse-to-fine. The first scheme transmits and renders the region of interest (ROI) of volume data on the client site at highest resolution for the first time, and consequently it iteratively expands the region layer by layer towards to the peripheral. While the second one gives a complete image in a low resolution for the first time on the client. The detail coefficients will be transmitted continuously and the rendering result will be progressively refined depending on the distance to the ROI. 1

this paper. For authenticating a particular volume data-set, the following steps are performed: Affine transformation parameters recovery: Since, one of the benign manipulations could be the affine transformation of the volume, the transform parameters are computed first. Matching: The content features of the transformed volume are compared with the content features of the original data-set (obtained from the digital signature after decryption using the owner's public key). A match value between the original features and the transformed volume features is computed. If this match value exceeds a certain threshold, then the volume is certified as genuine else it is considered untrustworthy. We have conducted experiments on two volume data sets, SKULL (## # ## # ##) and TOMATO (## # ### # ###) (Figure 2). In the selection of key voxels, we used a windowed lowpass filtering for five times with the window size 9 and the threshold 1.5. The resulting numbers of key voxels are 25 for SKULL and 124 for TOMATO. The sizes of the signatures are 8KB and 19KB respectively. Five experiments were done with these two volume data sets. The first three experiments examine the signature robustness under global manipulation like low-pass filtering, sharpening, and lossy compression, whereas the last two experiments consider local manipulation like cropping and localized modification. One experiment result of adding Gaussian noise is shown in Figure 3. In this experiment, for SNR of the noise as low as 14.70dB, the volume was still authenticated. Other experimental results are also promising

3D volume data has been increasingly used in many applications. The digital nature

Foveation principles suggested by natural vision systems enable the construction of a proper mask that may modulate the coefficients given by the Discrete Wavelet Transform of an ECG record. The mask is spatially selective and provides maximum accuracy around specific regions of interest. Subsequent denoising and coefficient quantization are further combined with efficient coding techniques such as SPIHT in order to provide high compression ratios at low reconstruction errors. Experimental results reported on a number of MIT-BIH records show improved performances over existing solutions Keywords: Foveation, 2D DWT, compression, ECG. 1.