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In baseball, the strike zone plays an important role in each pitch. Pitches which pass through the strike zone count as strikes, three of which strike out the batter. Thus, pitchers should acquire mastery of the strike zone. Moreover, the strike zone also provides the reference for positioning the pitch locations, about which sports fans and professionals have an intense interest in compile statistics...
Monitoring multimodal data generated by sensor networks for extracting information is a challenging task for the human observer. To manage the barrage of data, one needs to create mechanisms for identifying only those time intervals which are informative and worthy of further highlevel analysis either by machine or the human observer. We regard a time interval to be informative and contain an event...
We investigate exploiting the class specific information in the conventional perceptual edge grouping for the task of object extraction, since the domain information is usually available in practice. Instead of applying the classical Gestalt principles, we turn to learn a class specific probabilistic structure model from training images. During the learning, both geometrical and photometric features...
Can we take advantage of the huge number of online images to improve image search quality? Motivated by this question, we propose a novel model to re-rank Google image search results by exploring the latent characteristic of massive unrelated images as a clue to filter them in the reranking. Inspired by the characteristic of the intrinsic diversity and the unwanted availability of the unrelated images,...
With popularization of multimedia devices, semantic analysis of sports video has been widely studied. In this paper, we propose a highlight generation method for basketball games. To create a video highlight, the proposed method selects interesting shots by modeling excitements of the game using score information. For this purpose, a video is first segmented into shots and classified as play and nonplay...
Logo detection is important for brand advertising and surveillance applications. The central issues of this technology are fast localization and accurate matching. Based on key traits analysis of common logos, this paper presents a two-stage detection scheme based on spatialspectral saliency (SSS) and partial spatial context (PSC). SSS speeds up logo location and avoid the impact of cluttered background...
This paper presents a new algorithm for moving object detection in the H.264/AVC compressed domain which relies on motion vector information. In contrast to other motion vector-based algorithms, special attention is paid to noisy motion vectors as they highly decrease the performance of these algorithms. We propose to estimate the reliability of motion vectors by comparing them with projected motion...
In the past few years, several research works have addressed the problems posed by vision-assisted navigation systems. Basically, these systems allow a tourists navigating in an urban environment to take the photograph of a scene and submit it to the navigation system that will recognize what monument is represented in the photograph. However, solutions proposed so far focus on the recognition of...
In this work, we propose a modified Hilbert-Huang transform (HHT) method to detect low pitch musical signals within a short analysis temporal window for real-time fundamental frequency estimation. HHT is a non-linear method which is suitable for the analysis of non-stationary AM/FM like data. However, to apply HHT directly to music signals encounters several problems. Here, we modify HHT so that it...
Visual event detection in video streams allows easier access to, and better organization of large media collections. This paper presents an event detection framework with a novel feature that incorporates flow, appearance and trajectory information jointly. While previous event detection methods have been designed for understanding human behaviours where the camera is either static or with minimal...
Target tracking based restrictively on acoustic and electromagnetic (EM) sensors may not provide adequate information regarding the mobile target. Hence, imaging sensors can be used to provide visual information. This paper develops an image-based tracking approach based on epipolar geometry and Kalman filtering. A corner detection technique is used to identify the prominent features in the frame...
Online social media sharing Web sites like Flickr allow users to manually annotate images with tags, which can facilitate image search and organization. However, the tags provided by users are often imprecise and incomplete, which severely limits the application of tags to image search and browse. In this paper, we propose a scheme to improve poorly annotated tags associated with social images. Two...
The paper attempts the recognition of multiple drivers' emotional state from physiological signals. The major challenge of the research is the severe inter-subject variation such that it is extreme difficult to build a general model for multiple drivers. In this paper, we focus on discovering an optimal feature mapping by utilizing the additional attribute from the drivers. Two models are reported,...
In this paper, we present a novel approach for human activities recognition in the video. We analyze human activities in the sequential frames because human activities can be considered as a temporal object which contains a series of frames. Firstly, we establish a statistical background model and extract foreground object through background subtraction in the video stream. Then, we use foreground...
This paper investigates the possibility of extracting latent aspects of a video, using visual information about humans (e.g. actors' faces), in order to develop a fingerprinting (replica detection) framework. We employ a generative probabilistic model, namely Latent Dirichlet Allocation (LDA), so as to capture latent aspects of a video, using facial semantic information derived from the video. We...
Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. In this paper, we present an approach based on probabilistic latent semantic analysis (PLSA) to accomplish the tasks of semantic image annotation and retrieval. In order to model training images precisely, we employ two PLSA models to capture semantic information from visual and textual...
This paper addresses the novel problem of characterizing conversational group dynamics. It is well documented in social psychology that depending on the objectives a group, the dynamics are different. For example, a competitive meeting has a different objective from that of a collaborative meeting. We propose a method to characterize group dynamics based on the joint description of a group members'...
A Hidden Markov Model (HMM) approach to off-line signature verification is presented. First, each of the signature images is represented as a landmark point set, which includes turning points, isolated points, trifurcate points, intersection points and termination points on signature skeleton. Then we propose a novel deformable grid partition technique. Based on landmark point matching, we build the...
Event-related query is playing a more and more important role in video retrieval. However, it is still a challenge to the existing video retrieval engines for lacking the effective motion analysis. In this paper, we propose a novel re-ranking scheme for video retrieval based on motion region trajectory analysis. By focusing on the changes of the primary moving regions, we construct an intuitive motion...
Many musical genres and styles are characterized by distinct representative rhythmic patterns. In most automatic genre classification systems global statistical features based on timbral dynamics such as mel-frequency cepstral coefficients (MFCC) are utilized but so far rhythmic information has not so effectively been used. In order to extract bar-long unit rhythmic patterns for a music collection...
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