Earticle

We present a gait recognition system using infra-red (IR) images. Since an IR camera is not affected by the intensity of illumination, it is able to provide constant recognition performance regardless of the amount of illumination. Model-based object tracking algorithms enable robust tracking with partial occlusions or dynamic illumination. However, this algorithm often fails in tracking objects if strong edge exists near the object. Replacement of the input image by an IR image guarantees robust object region extraction because background edges do not affect the IR image. In conclusion, the proposed gait recognition algorithm improves accuracy in object extraction by using IR images and the improvements finally increase the recognition rate of gaits.

Automatic video segmentation plays an important role in real-time MPEG-4 encoding systems. This paper presents a video segmentation algorithm for MPEG-4 camera system with change detection, background registration techniques and real time adaptive threshold techniques. This algorithm can give satisfying segmentation results with low computation load. Besides, it has shadow cancellation mode, which can deal with light changing effect and shadow effect. Furthermore, this algorithm also implemented real time adaptive threshold techniques by which the parameters can be decided automatically.

In this paper, we present comparative analysis of scale-invariant feature extraction using different wavelet bases. The main advantage of the wavelet transform is the multi-resolution analysis. Furthermore, wavelets enable localization in both space and frequency domains and high-frequency salient feature detection. Wavelet transforms can use various basis functions. This research aims at comparative analysis of Haar, Daubechies and Gabor wavelets for scale-invariant feature extraction. Experimental results show that Gabor wavelets outperform better than Haar, Daubechies wavelets in the sense of both objective and subjective measures.

As camera phones have permeated into our everyday lives, two dimensional (2D) barcode has attracted researchers and developers as a cost-effective ubiquitous computing tool. A variety of 2D barcodes and their applications have been developed. Often, only monochrome 2D barcodes are used due to their robustness in an uncontrolled operating environment of camera phones. However, we are seeing an emerging use of color 2D barcodes for camera phones. Nonetheless, using a greater multitude of colors introduces errors that can negatively affect the robustness of barcode reading. This is especially true when developing a 2D barcode for camera phones which capture and store these barcode images in the baseline JPEG format. This paper presents one aspect of the errors introduced by such camera phones by modeling the camera phone capture channel for JPEG color barcode images wherein there is camera auto-focus.

With the development of mobile technology, Internet and GIS, LBS plays an important role in various applications. In this paper, we present our work on this area. The LaMOC1system, a location based mobile spatial cooperative system with cooperative and spatial group decision supported characters, developed by ICA-ECNU is presented. LaMOC is a Location Based System, a Mobile Cooperative System and a Spatial Group Decision Support System. A map based co-browser is designed as user interface. The design of the LaMOC, its system architecture, user interface, and key issues are discussed here.

The resolution of multy variable complex problems such as the multy speaker speech recognition and independently of context, requires the application of neural structures. One tool which proves to be powerful in the classification field, is the kohonen map called SOM. This map is characterized by the representation of static data. Thus, we ought to enrich the intelligibility and the performance of this model in order to reach what biology imposes by handling a kind of logical pile "memory" with the introduction of temporal context which realise feedbacks that integrate respectively the leaky integrators concept for the TKM. The recurrent leaky integrators idea for the recurrent SOM ‘RSOM’ in an improvement of the TKM. More recently, the principle of self reference for the recursive SOM. In other case, we are introducing the possibility to obtain hybridization with GA in an attempt to reach the natural evolution of the human thought as regards to recognition.

In this paper, we address issues associated with the real-time implementation of upmixing stereo audio into 5.1 channel audio in order to improve audio realism. First, we review four different upmixing methods, including a passive surround decoding method, a least-meansquare based upmixing method, a principal component analysis based upmixing method, and an adaptive panning method. After that, we implement a simulator that includes the upmixing methods and audio controls to play both stereo and upmixed 5.1 channel audio signals. Finally, we carry out a MUSHRA test to compare the quality of the upmixed 5.1 channel audio signals to that of the original stereo audio signal. It is shown from the test that the upmixed 5.1 channel audio signals generated by the four different upmixing methods are preferred to the original stereo audio signals.

This paper presents a novel approach to reducing ringing artifact in digitally restored images by using multi-resolution edge map. The performance of reducing ringing artifacts depends on the accurate classification of the local features in the image. The discrete wavelet transform (DWT) provides effective insight into both spatial and frequency characteristics of an image. Through the DWT analysis, we show that ringing artifacts can be suppressed to a great extent by using multiple-level edge maps, which provide enhanced matching to local edges. Base on the experimental results, the proposed method can reduce ringing artifacts with minimized edge degradation by using DWT analysis.