17076982
A new key frame representation for video segment retrieval
In this paper, we propose an optimal key frame representation scheme based on global statistics for video shot retrieval. Each pixel in this optimal key frame is constructed by considering the probability of occurrence of those pixels at the corresponding pixel position among the frames in a video shot. Therefore, this constructed key frame is called temporally maximum occurrence frame (TMOF), which is an optimal representation of all the frames in a video shot. The retrieval performance of this representation scheme is further improved by considering the k pixel values with the largest probabilities of occurrence and the highest peaks of the probability distribution of occurrence at each pixel position for a video shot. The corresponding schemes are called k-TMOF and k-pTMOF, respectively. These key frame representation schemes are compared to other histogram-based techniques for video shot representation and retrieval. In the experiments, three video sequences in the MPEG-7 content set were used to evaluate the performances of the different key frame representation schemes. Experimental results show that our proposed representations outperform the alpha-trimmed average histogram for video retrieval.
39178482
Illumination invariant face recognition
The appearance of a face will vary drastically when the illumination changes. Variations in lighting conditions make face recognition an even more challenging and difficult task. In this paper, we propose a novel approach to handle the illumination problem. Our method can restore a face image captured under arbitrary lighting conditions to one with frontal illumination by using a ratio-image between the face image and a reference face image, both of which are blurred by a Gaussian filter. An iterative algorithm is then used to update the reference image, which is reconstructed from the restored image by means of principal component analysis (PCA), in order to obtain a visually better restored image. Image processing techniques are also used to improve the quality of the restored image. To evaluate the performance of our algorithm, restored images with frontal illumination are used for face recognition by means of PCA. Experimental results demonstrate that face recognition using our method can achieve a higher recognition rate based on the Yale B database and the Yale database. Our algorithm has several advantages over other previous algorithms: (1) it does not need to estimate the face surface normals and the light source directions, (2) it does not need many images captured under different lighting conditions for each person, nor a set of bootstrap images that includes many images with different illuminations, and (3) it does not need to detect accurate positions of some facial feature points or to warp the image for alignment, etc.
5893059
Hybrid Chinese/English text detection in images and video frames
We propose a multiscale texture-based method using local energy analysis for hybrid Chinese/English text detection in images and video frames. Local energy analysis has been shown to work well in text detection, where remarkable local energy variations of pixels correspond to text region or boundary of other objects and lower local energy variations of pixels correspond to background or the interior of non-text objects. Local energy variation is calculated in a local region based on the wavelet transform coefficients of images. Hybrid Chinese/English text in images and video frames can be detected whether it is aligned horizontally or vertically. The font size of text to be detected may vary in a wide range of values. The proposed method has been tested on 321 frame images obtained from local TV programs and a tested dataset with low missed rate and false alarm rate.
26133489
Robust Hausdorff distance for shape matching
The Hausdorff distance can be used to measure the similarity of two point sets. In matching the two point sets, one of them is translated, rotated and scaled in order to obtain an optimal matching, which is a computationally intensive process. In this paper, a robust line-feature-based approach for model-based recognition is presented, which can achieve good matching, even in a noisy environment or with the existence of occlusion. We propose three different ways for forming the line segments for a point set. Two of the methods are based on a fixed reference point, which are the centroid and the center of the minimal disk of the point set. The third method is based on the longest possible line segments formed within the point set. The line features extracted based on the respective line segments are insensitive to noise and can be used to determine the rotation and scale of the image point set accurately and reliably, and more importantly, 2D-2D matching algorithm can be adopted. The first 2D-matching is to compute the relative scale and orientation between the two point sets. Having rotated and scaled the image point set, the M-Estimation Hausdorff distance is applied for the second 2D-matching to measure the relative translation between the query point set and the model point set. This 2D-2D matching can greatly reduce the required memory and computation when compared to a 4D-matching. Both the performance and the sensitivity to noise of our algorithms are evaluated using simulated data. Experiments show that our 2D-2D algorithms can yield a high level of performance when determining the scale, the orientation and the similarity of two point sets.
28287084
Human face recognition based on spatially weighted Hausdorff distance
The edge map of a facial image contains abundant information about its shape and structure, which is useful for face recognition. To compare edge images, Hausdorff distance is an efficient measure that can determine the degree of their resemblance, and does not require a knowledge of correspondence among those points in the two edge maps. In this paper, a new modified Hansdorff distance measure is proposed, which has a better discriminant power. As different facial regions have different degrees of significance for face recognition, a new modified Hausdorff distance is proposed which is weighted according to a weighted function derived from the spatial information of the human face; hence crucial regions are emphasized for face identification. Experimental results show that the distance measure can achieve recognition rates of 80%, 87%, and 91% for the first, the first five, and the first seven likely matched faces, respectively.
209064801
An accurate active shape model for facial feature extraction
17015154
Priority and deadline assignment to triggered transactions in distributed real-time active databases
Abstract A distributed real-time active database system (DRTADBS) reacts to the critical events that occurred in the external environment by triggering of transactions. In this paper, the priority and deadline assignment to triggered transactions under two coupling modes, the deferred and immediate, in a DRTADBS is discussed. Two new approaches, the data state dependent (DSD) and the transaction-data deadline (TDD), are proposed to assign criticality and deadlines to the triggered transactions, respectively. In the DSD approach, the criticality of a triggered transaction is defined according to the state of the temporal data object which is responsible for its triggering. The objective of the DSD approach is to increase the number of commit achieved by the triggered transactions especially the more critical ones. The performance of these two approaches under the two coupling modes has been investigated. The results show that the DSD approach is more effective under the immediate coupling mode than under the deferred coupling mode due to the late creation of the triggered transactions under the deferred coupling mode. The TDD approach can improve the system performance under both deferred and immediate coupling mode.
32532096
A Priority Feedback Mechanism for Distributed MPEG Video Player Systems
In this paper, a priority feedback mechanism is proposed for adjusting the priorities of the processes dynamically in a video server according to the current status of the clients — the status can be reflected by the number of frames being dropped in a period of time. The priority feedback mechanism is implemented in a distributed MPEG video player system. Different priority mapping functions are suggested for the priority feedback mechanism to cater for different service requirements of the clients, especially when the clients are demanding different quality of services. Experiment results have shown that when the video server is serving several clients where every client may demand a play speed of their own, the use of the priority feedback mechanism can effectively improve the whole system performance.
16770370
Impact of priority assignment on optimistic concurrency control in distributed real-time databases
In the studies of real-time concurrency control protocols (RT-CCPs), it is always assumed that earliest deadline first (EDF) is employed as the CPU scheduling algorithm. However, using purely (ultimate) deadline for priority assignment may not be suitable for distributed real-time database systems (DRTDBS) in which there exist different kinds of transactions, such as global and local transactions. In order to improve the performance, different priority assignment heuristics have to be used. In this paper, we have investigated the performance of different priority assignment heuristics for sub-transactions in DRTDBS with optimistic concurrency control (OCC) protocol. If is found that the heuristics, which are suitable for distributed real-time systems, are not suitable for DRTDBS. We find that our proposed heuristic, which considers both deadline constraint and data contention, can give the best performance.
13891436
Adaptive Real-Time Monitoring Mechanism for Replicated Distributed Video Player Systems
One of the main problems to ensure the quality of services (QoS) in video playback in a replicated distributed video player system is how to adapt to the changing network traffic condition and the workload at the video servers. In this paper, we propose a mechanism, called adaptive real-time monitoring, to solve the problem. The proposed mechanism consists of three steps: selection, monitoring and switching. In the selection step, the mechanism will determine which video server to serve the client by considering the factors of the current network traffic and workload at the servers. In the monitoring step, the QoS of the video playback will be monitored closely. A feedback mechanism is adopted to improve the QoS of video playback by adjusting the allocation of resources at the video server. The switching mechanism will be invoked when the QoS of the video display is too worse that it must switch to another video server.
8870380
Performance analysis of three related assignment problems
The relative placement of records in a database has a significant impact on the overall system performance. In this paper we study three related assignment problems. They are (1) the assignment of records to devices so as to minimize the expected completion time and to maximize the expected utilization of the devices, (2) the assignment of records to pages or blocks in secondary memory so as to minimize the number of blocks to be accessed, and (3) the analysis of the performance of a hashing scheme under the assumption that the record-to-bucket probability varies from one bucket to another. The solutions to these problems are obtained by studying an occupancy problem. In each case, an optimal solution is obtained.