30893886
Delay Defect Characterization Using Low Voltage Test
For nanometer designs, many subtle defects lead to excessive delays in signal paths that cause reliability concerns. Traditional test-based diagnosis methods can only identify the failing nodes without the capability to tell the defect nature behind the observed delay faults. This differentiation is important for gathering accurate defect statistics for process improvement during yield ramp-up. In this paper we presented an effective delay defect analysis methodology that can quickly categorize the delay defects into either transistor related defects or resistive interconnect defects. The new delay defect/failure characterization method is based on low voltage test and delay defect detection in slack interval (DDSI) method. Experimental results were presented to validate the effectiveness of the new method. Practical considerations were also addressed for adoption of the methodology.
8459751
Low voltage test in place of fast clock in DDSI delay test
By testing the CUT at lower supply voltages, the CUT slows down and thus slow, low-cost testers can be used to perform DDSI (defect detection within slack intervals) tests. Apart from this, because the delay fault size is known in a DDSI test, this information can be further used to diagnose the causing mechanism behind the delay faults. Experimental results are presented to investigate the potential of the method.
9210608
Delay Test Scan Flip-Flop: DFT for High Coverage Delay Testing
Scan based delay testing is currently mostly implemented using launch-on-capture (LOC) delay tests. Launch-on-shift (LOS) tests are generally more effective, achieving higher fault coverage with significantly fewer test vectors, but require a fast scan enable, which is not supported by most designs. The paper presents low cost solution for implementing LOS tests by adding a small amount of logic (six transistors) in each flip-flop to align the slow scan enable signal to the clock edge. The new design can support full LOS and LOC testing, achieving an average TDF coverage of 92.67% in this combined mode for the ISCAS89 benchmarks. Adding a second slow global scan enable signal also allows mixed LOC/LOS tests, which can further increase coverage up to 94.86% on average for ISCAS89 benchmarks
18688072
Human action recognition with primitive-based coupled-HMM
This paper presents a new approach named primitive-based coupled-HMM for human natural complex action recognition. First, the system proposes a hybrid human model and employs 2-order B-spline function to detect the two shoulder joints in the silhouette image to obtain the basic motion features including the elbow angles, motion parameters of the face and two hands. Then, primitive-based coupled hidden Markov model (PCHMM) is presented for natural context-dependent action recognition. Lastly, comparison experiments show that PCHMM is better than the conventional HMM and coupled HMM.
3175759
Regular algebraic curve segments (I) - Definitions and characteristics
Abstract In this paper (part one of a trilogy), we introduce the concept of a discriminating family of regular algebraic curves (real, nonsingular and connected). Several discriminating families are obtained which yield different characterizations of the Bernstein–Bezier (BB) bivariate polynomials over the plane triangle and the quadrilateral domain such that their zero contours are smooth and connected. These regular curve segments in BB basis can be smoothly joined together to form algebraic curve splines or A-splines. Algorithms for the efficient graphics display of these new A-spline families are also provided.
718597
Error bounded regular algebraic spline curves
i=0 Pn n=0 bijB m i (u)B n j (v) of bi-degree (m;n) has total degree m + n, however, the class of Gmn(u; v) is a subset of polynomials of total degree m + n. G (resp G) continuity implies curve segments share the same tangent(curvature) at join points(knots). In each of the G and G constructions, we develop a spline curve family whose member satis es given interpolation conditions. Each family depends on one free parameter that is related linearly to coe cients of Gmn(u; v). Compared with A-spline segments de ned in triangular (barycentric) BB-form [2], these algebraic curve segments in tensor product form have the following distinct features: (a) They are easy to construct. The coe cients of the bivariate polynomial that de ne the curve are explicitly given. (b) There exist convenient geometric control handles to locally modify the shape of the curve, essential for interactive curve design. (c) The spline curves, for the rectangle scheme, are -error controllable where is the prespeci ed width of the rectangle. This feature is especially important for tting to \noisy" data with uncertainty. (d) These splines curves have a minimal number of in ection points. Each curve segment of the spline curve has either no in ection points if the corresponding edge is convex, or one in ection point otherwise, and the join points of the curve segments are not in ection points. (e). Since the required bi-degree (m;n) for G and G is low(in this paper, minfm;ng 2), the curve can be evaluated and displayed extremely fast. We explore both display via parameterization as well as recursive subdivision techniques(see [11]). (f) In the six spline families we discuss in sections 2 and 3, there are four cases with minfm;ng = 1. In these cases, rational parametric expressions are easily derived. Hence, for
18125681
A Speaker Tracking Algorithm Based on Audio and Visual Information Fusion Using Particle Filter
Object tracking by sensor fusion has become an active research area in recent years, but how to fuse various information in an efficient and robust way is still an open problem. This paper presents a new algorithm for tracking speaker based on audio and visual information fusion using particle filter. A closed-loop architecture with reliability of each individual tracker is adopted, and a new method for data fusion and reliability adjustment is proposed. Experiments show the new algorithm is efficient in fusing information and robust to noise.
14215306
Hidden Markov Model Based Events Detection in Soccer Video
This paper presents an algorithm developed based on hidden Markov model for cues fusion and event inference in soccer video. Four events, shoot, foul, offside and normal playing, are defined to be detected. The states of the events are employed to model the observations of the five cues, which are extracted from the shot sequences directly. The experimental results show the algorithm is effective and robust in inferring events from roughly extracted cues.