Abstract: This paper describes an algorithm to estimate realtime vehicle velocity using image processing technique from the known camera calibration parameters. The presented algorithm involves several main steps. First, the moving object is extracted by utilizing frame differencing technique. Second, the object tracking method is applied and the speed is estimated based on the displacement of the object-s centroid. Several assumptions are listed to simplify the transformation of 2D images from 3D real-world images. The results obtained from the experiment have been compared to the estimated ground truth. From this experiment, it exhibits that the proposed algorithm has achieved the velocity accuracy estimation of about ± 1.7 km/h.
Abstract: This paper presented the potential of smart phone to
provide support on mapping the indoor asset. The advantage of using
the smart phone to generate the indoor map is that it has the ability to
capture, store and reproduces still or video images; indeed most of us
do have this powerful gadget. The captured images usually used by
maintenance team to save a record for future reference. Here, these
images are used to generate 3D models of an object precisely and
accurately for efficient and effective solution in data gathering. Thus,
it could be a resource for an informative database in asset
management.
Abstract: Freeways are originally designed to provide high
mobility to road users. However, the increase in population and
vehicle numbers has led to increasing congestions around the world.
Daily recurrent congestion substantially reduces the freeway capacity
when it is most needed. Building new highways and expanding the
existing ones is an expensive solution and impractical in many
situations. Intelligent and vision-based techniques can, however, be
efficient tools in monitoring highways and increasing the capacity of
the existing infrastructures. The crucial step for highway monitoring
is vehicle detection. In this paper, we propose one of such
techniques. The approach is based on artificial neural networks
(ANN) for vehicles detection and counting. The detection process
uses the freeway video images and starts by automatically extracting
the image background from the successive video frames. Once the
background is identified, subsequent frames are used to detect
moving objects through image subtraction. The result is segmented
using Sobel operator for edge detection. The ANN is, then, used in
the detection and counting phase. Applying this technique to the
busiest freeway in Riyadh (King Fahd Road) achieved higher than
98% detection accuracy despite the light intensity changes, the
occlusion situations, and shadows.
Abstract: This paper suggests an improved integer frequency
offset (IFO) estimation scheme using P1 symbol for orthogonal
frequency division multiplexing (OFDM) based the second generation
terrestrial digital video broadcasting (DVB-T2) system. Proposed
IFO estimator is designed by a low-complexity blind IFO estimation
scheme, which is implemented with complex additions. Also, we
propose active carriers (ACs) selection scheme in order to prevent
performance degradation in blind IFO estimation. The simulation
results show that under the AWGN and TU6 channels, the proposed
method has low complexity than conventional method and almost
similar performance in comparison with the conventional method.
Abstract: More and more home videos are being generated with the ever growing popularity of digital cameras and camcorders. For many home videos, a photo rendering, whether capturing a moment or a scene within the video, provides a complementary representation to the video. In this paper, a video motion mining framework for creative rendering is presented. The user-s capture intent is derived by analyzing video motions, and respective metadata is generated for each capture type. The metadata can be used in a number of applications, such as creating video thumbnail, generating panorama posters, and producing slideshows of video.
Abstract: We present a new method to reconstruct a temporally
coherent 3D animation from single or multi-view RGB-D video data
using unbiased feature point sampling. Given RGB-D video data, in
form of a 3D point cloud sequence, our method first extracts feature
points using both color and depth information. In the subsequent
steps, these feature points are used to match two 3D point clouds in
consecutive frames independent of their resolution. Our new motion
vectors based dynamic alignement method then fully reconstruct
a spatio-temporally coherent 3D animation. We perform extensive
quantitative validation using novel error functions to analyze the
results. We show that despite the limiting factors of temporal and
spatial noise associated to RGB-D data, it is possible to extract
temporal coherence to faithfully reconstruct a temporally coherent
3D animation from RGB-D video data.
Abstract: In this paper, we employ the approach of linear
programming to propose a new interactive broadcast method. In our
method, a film S is divided into n equal parts and broadcast via k
channels. The user simultaneously downloads these segments from k
channels into the user-s set-top-box (STB) and plays them in order.
Our method assumes that the initial p segments will not have
fast-forwarding capabilities. Every time the user wants to initiate d
times fast-forwarding, according to our broadcasting strategy, the
necessary segments already saved in the user-s STB or are just
download on time for playing. The proposed broadcasting strategy not
only allows the user to pause and rewind, but also to fast-forward.
Abstract: Motion estimation is the most computationally
intensive part in video processing. Many fast motion estimation
algorithms have been proposed to decrease the computational
complexity by reducing the number of candidate motion vectors.
However, these studies are for fast search algorithms themselves while
almost image and video compressions are operated with software
based. Therefore, the timing constraints for running these motion
estimation algorithms not only challenge for the video codec but also
overwhelm for some of processors. In this paper, the performance of
motion estimation is enhanced by using Intel's Streaming SIMD
Extension 2 (SSE2) technology with Intel Pentium 4 processor.
Abstract: Routing places an important role in determining the
quality of service in wireless networks. The routing methods adopted
in wireless networks have many drawbacks. This paper aims to
review the current routing methods used in wireless networks. This
paper proposes an innovative solution to overcome the problems in
routing. This solution is aimed at improving the Quality of Service.
This solution is different from others as it involves the resuage of the
part of the virtual circuits. This improvement in quality of service is
important especially in propagation of multimedia applications like
video, animations etc. So it is the dire need to propose a new solution
to improve the quality of service in ATM wireless networks for
multimedia applications especially during this era of multimedia
based applications.