This paper proposes an intelligent vehicle system (ITS) to monitor the driver driving behavior. Based on the first-person vision (FPV) technology (or Google glasses), our system can detect the vehicle exterior/interior scene from driver’s viewpoint and estimate driver gazing direction. First, we use “bag of words” image classification approach by applying FAST and BRIEF feature descriptor in the dataset. Then, we use vocabulary dictionary to encode an input image as feature vectors. Finally, we apply SVM classifier to identify whether the input image is vehicle interior scene or not to monitor the driver driving attention. Second, we find the correspondence between the images of the Google glasses and the camera mounted on the wind shield of the vehicle to estimate the gazing direction of the driver. In the experiments, we illustrate the effectiveness of our system.
This paper proposed an effective overtaking vehicle detection and localization system based on wheel detection. Using the windshield-mounted camera, it can detect the vehicles in rear-view and side-view. It extracts the MB-LBP feature for the cascaded Adaboost classifiers. Differing from traditional approaches, our method can overcome the perspective variation of the wheels in the images. It can detect the wheels of different aspect rations with varying scales. After wheel detection, it can locate the overtaking vehicle by pairing the front/rear wheels. The experiments show that our system can identify and locate the vehicle appearing in side-view as well as in rear-view. The performance of wheel detector is demonstrated with the precision rate as 0.91 and recall rate as 0.96.
This paper proposes a multi-PTZ-camera control mechanism to acquire close-up imagery of human objects in a surveillance system. The control algorithm is based on the output of multi-camera, multi-target tracking. Three main concerns of the algorithm are (1) the imagery of human object’s face for biometric purposes, (2) the optimal video quality of the human objects, and (3) minimum hand-off time. Here, we define an objective function based on the expected capture conditions such as the camera-subject distance, pan tile angles of capture, face visibility and others. Such objective function serves to effectively balance the number of captures per subject and quality of captures. In the experiments, we demonstrate the performance of the system which operates in real-time under real world conditions on three PTZ cameras.
In this paper, we introduce a real time vision-based human motion capturing system using two CCD cameras. For realtime
processing consideration, we propose some simple but effective methods to estimate the motion parameters (BAPs)
of the human object. Our method analyzes the vertical projection profile and the horizontal projection profile in each
view to identify different arm and leg postures. With the identified postures, we can apply the Kalman filter to track the
motion parameters (joint angels). Our motion analysis method is divided into macro motion analysis and micro motion
analysis. The former identifies certain well-defined postures and the latter traces the variation of joint angle or BAPs.
SiNx films were prepared by rf reactively sputtering. The refractive index of SiNx films was affected by total pressure and sputtering power. When the total pressure increased, the refractive index decreased. The reduction of sputtering power showed similar effect to raise the total gas pressure. The residual stress and roughness of SiNx films depended on the total pressure, sputtering power, and the thickness. The thermal cycles may result in irreversible change of residual stress of SiNx film. The magnetic properties of TbFeCo depended on the residual stress and roughness of SiNx in the trilayer SiNx/TbFeCo/SiNx samples. The coercivity of TbFeCo was enhanced in the samples with SiNx films having low stress and large roughness.
This paper proposes a new ADPCM method for image coding called directional ADPCM which can remove more redundancy from the image signals than the conventional ADPCM. The conventional ADPCM calculates the two-dimensional prediction coefficients by using the correlation functions followed by solving the Yule-Walker equation. Actually, the quantities of correlation functions to be the approximation of the correlation function. However, the block size is limited by the error accumulation effect during packet transmission. Using small block may induce the unregulated prediction coefficients. Therefore, we need to develop the directional ADPCM system to overcome such a problem and to have better prediction result. Our directional ADPCM utilized the fan- shape filters to obtain the energy distribution in four directions and then determines the four directional prediction coefficient. All the fan-shape filters are designed by using the singular value decomposition (SVD) method, the two-dimensional Hilbert transform technique, and the frequency weighting concept. In the experiments, we illustrate that the M.S.E. for the directional ADPCM is less than that of the conventional ADPCM.
This paper proposes a new ADPCM method for image coding called directional ADPCM which can remove more redundancy from the image signals than the conventional ADPCM. The conventional ADPCM calculates the two-dimensional prediction coefficients by using the correlation functions and solving the Yule-Walker equation. Actually, the quantities of correlation functions are replaced by the sample averages. Therefore, this solution will not be optimum. Our directional ADPCM utilizes the directional filters to obtain the energy distribution in four directions and then determines the four directional prediction coefficients. All the directional filters are designed by using the singular value decomposition (SVD) method and the two-dimensional Hilbert transform technique. In the experiments, we illustrate that the M.S.E. for the directional ADPCM is less than that of the conventional ADPCM.
In image wrapping, the post-filtering is necessary to avoid aliasing effect. Here, we develop a hybrid space-variant directional filtering for post-processing. In order to reduce the computation, we classify the filter area as three blocks: constant, oriented, and irregular. The constant and irregular blocks are local average filtering and elliptical weighted average filtering. In oriented model, we propose a new filtering method called elliptical weighted adaptive directional moving average filter. In the experiments, we show that our method may correct the distorted images and have better results, with better subjective quality, especially with high magnification ratio, such as four times or more.
This paper proposes a new motion-compensated frame (field) interpolation algorithm for frame (field) rate upconversion, which allows us to interpolate frame (or pairs of fields) between two originally continuous frames (fields) of a digital television sequence by preserving the stationary background. First, for a interlace format, the de-interlacing process was used to reduce the motion range after converting the interlace format to progressive one. A video scene can be temporally categorized by the change detector into changed and unchanged regions. Each changed region is further separated into moving objects, covered and uncovered regions. To interpolate the intermediate field (frame), we have developed direct motion interpolation method and indirect motion interpolation method to fill the moving object areas in the changed regions, and then apply the forward/backward motion extrapolation method to fill the covered/uncovered regions. Finally the hybrid repetition is used to interpolate the unchanged regions. In the experiment, we will show the interpolated fields and frames for two standard image sequences.
In this paper, we develop a directional 2-D non-separable filter bank which can perform the perfect reconstruction of the downsampled subband signals. The filter bank represents a union of two powerful image and video processing tools: directional decomposition and subband decomposition. This subband decomposition is implemented by: (1) shifting the input signal and the subband signals; (2) using a tree-structure diamond shape prefilter followed by downsampling on quincunx grids; and (3) applying four types parallelogram prefilters followed by four different downsampling matrices respectively. This paper addresses the design and implementation of two-channel filter banks for such applications. The two-band subsystem in the tree-structure filter bank is proved and analyzed to be able to provide perfect reconstruction of the downsampled subband signals. Our method is extremely computationally simple in designing the analysis/synthesis subfilters for the filter bank without using any nonlinearly constrained numerical optimization. Finally, we use conventional 1-D analysis/synthesis filters as prototype and then apply McClellan transform for the specific 2-D diamond shape and parallelogram shape sub-filters.
This paper presents a new hybrid method that combines the scale space filter (SSF) and Markov random field (MRF) for color image segmentation. Using the scale space filter, we separate the different scaled histogram to intervals corresponding to peaks and valleys. The basic construction of MRF is a joint probability given the original data. The original data is the image that we get from the source and the result is called the label image. Because the MRF needs the number of segments before it converges to the global minimum, we exploit the scale space filter to do coarse segmentation and then use MRF to do fine segmentation of the images. Finally, we compare the experimental results obtained from using SSF only, or combined with MRF using iterated conditional mode (ICM) and Gibbs sampling.
The aspect graph is basically a multiple-view representation of the designated 3-D object. In this paper, we present a complete algorithm for constructing the aspect graph of non-convex polyhedral objects from perspective point of view.
Sign Language is a better language used by the hearing impaired. This report offers a means of visual communication over a very—low bandwidth communication network (i.e. telephone lines) of which the purpose is to supply a visual telecommunication among the deaf community. We develop a system which consists of the edge detection, the binarization, the vectorization, the inter—frame correspondence, the component trajectory finding, and hybrid encoding. This system is able to transmit a sequence of images of the sign language at higher resolution and lower transmission rate.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.