6309219
Contextual browsing for highlights in sports video
A novel highlight browsing approach for sports videos, based on contextual cue categorization, is proposed in this paper. Contextual cues are those salient audio and visual cues around highlight segments, and they are also informative and attractive to audiences. With further analysis and categorization of these contextual cues, the user could access highlights more flexibly and effectively. An experimental system is built for broadcasting diving videos in our current work, in which contextual cues such as slow-motion replays and game statistics information are extracted and categorized for highlight browsing. An efficient algorithm for slow-motion replay detection and categorization in diving videos is also proposed. Experimental results on 2 hours broadcasting diving videos have demonstrated the effectiveness and efficiency of the proposed approach.
28206858
Tennis Video Analysis Based on Transformed Motion Vectors
Motion Vectors (MV) indicate the motion characteristics between two video frames, and has been widely used in the content-based sports video analysis. Previous works on sports video analysis have proved the effectiveness and efficiency of the MV-based methods. However, in the tennis video, the MV-based methods are seldom applied because the motion represented by MV is greatly deformed relative to the player’s true movement due to the camera’s diagonal shooting. In this paper, an algorithm of MV transformation is proposed to revise the deformed MV using a pinhole camera model. With the transformed MVs, we generate the temporal feature curves and employ Hidden Markov Models to classify two types of player’s basic actions. Evaluation on four hours live tennis videos shows very encouraging results.
8406634
Cycles in 2-connected graphs
Let Gn be a class of graphs on n vertices. For an integer c, let ex(gn, c) be the smallest integer such that if G is a graph in Gn with more than ex(Gn, c) edges, then G contains a cycle of length more than c. A classical result of Erdos and Gallai is that if Gn is the class of all simple graphs on n vertices, then ex(Gn, c) = c/2 (n - 1). The result is best possible when n - 1 is divisible by c - 1, in view of the graph consisting of copies of Kc all having exactly one vertex in common. Woodall improved the result by giving best possible bounds for the remaining cases when n - 1 is not divisible by c - 1, and conjectured that if Gn is the class of all 2-connected simple graphs on n vertices, then ex(Gn, c) = max{f(n,2,c), f(n, ⌊c/2 ⌋,c)}, where f(n, t, c) = (c+1-t 2) + t(n - c - 1 + t), 2 ≤ t ≤ c/2, is the number of edges in the graph obtained from Kc+1-t by adding n-(c + 1 - t) isolated vertices each joined to the same t vertices of Kc+1-t. By using a result of Woodall together with an edge-switching technique, we confirm Woodall's conjecture in this paper.
2131320
An Integrated Architecture for Recognition of Totally Unconstrained Handwritten Numerals
Reprint. Reprinted from the International journal of pattern recognition and artificial intelligence. Vol. 7, no. 4 (1993) "January 1993."
15398175
Hardware-based Packet Classification Made Fast and Efficient
To achieve fast packet classification, a hardware-based scheme, cross-producting recurrence (CPR), based on a formerly proposed cross-producting scheme is proposed. This scheme simplifies the classification procedure and decrease the distinct combinations of fields by hierarchically decomposing the multi-dimensional space. In the new scheme, the multi-dimensional space is endowed with a hierarchical property which self-divides into several smaller subspaces, whereas the procedure of packet classification is translated into repeatedly searching for matching subspaces. The required storage of the proposed scheme is significantly reduced since the distinct fields of subspaces is controlled by a pre-defined configuration and can be much less than that of the filters. The experimental results demonstrate the effectiveness and scalability of the proposed scheme
25531643
Multicomponent chirp signals analysis using product cubic phase function
This paper presents an algorithm for estimating the parameters of multicomponent chirp signals. The estimator is based on the cubic phase function (CPF), which is efficient to estimate the parameters of monocomponent first-, second-, and third-order polynomial phase signal. When the CPF is dealing with multicomponent chirp signals, the spurious peaks arise and hence the identifiability problem exists. A new approach based on the product cubic phase function (PCPF) is proposed to remove the identifiability problem. The occurrence probability of spurious peak, and the effect of noise to the estimator are statistically studied. The simulation examples are provided for validating the theoretical analysis.
31996759
Analysis and Design of Parallel Thinning Algorithms - A Generic Approach
In this paper, a generic approach for the analysis and design of parallel thinning algorithms is presented. The procedures for designing 4-subcycle/iteration, 2-subcycle/iteration, and 1-subcycle/iteration thinning algorithms are developed. The experimental results show that these thinning algorithms designed by proposed approach preserve image connectivity, produce thinner results, and obtain faster speed than many existing key thinning algorithms. As an example, a 1-subcycle/iteration algorithm and its experimental results were illustrated, which is in general about two times faster than others in the literature.