Explicit contour model for vehicle tracking with automatic hypothesis validation

This paper addresses the problem of vehicle tracking under a single static, uncalibrated camera without any constraints on the scene or on the motion direction of vehicles. We introduce an explicit contour model, which not only provides a good approximation to the contours of all classes of vehicles but also embeds the contour dynamics in its parameterized template. We integrate the model into a Bayesian framework with multiple cues for vehicle tracking, and evaluate the correctness of a target hypothesis, with the information implied by the shape, by monitoring any conflicts within the hypothesis of every single target as well as between the hypotheses of all targets. We evaluated the proposed method using some real sequences, and demonstrated its effectiveness in tracking vehicles, which have their shape changed significantly while moving on curly, uphills roads. © 2005 IEEE.published_or_final_versionThe IEEE International Conference on Image Processing (ICIP 2005), Genoa, Italy, 11-14 September 2005. In Proceedings of IEEE-ICIP, 2005, v. 2, p. 582-58

Shadow detection for vehicles by locating the object-shadow boundary

We introduce in this paper a shadow detection method for vehicles in traffic video sequences. Our method approximates the boundary between vehicles and their associated shadows by one or more straight lines. These lines are located in the image by exploiting both local information (e.g. statistics in intensity differences) and global information (e.g. principal edge directions). The proposed method does not assume a particular lighting condition, and requires no human interaction nor parameter training. Experiments on practical real-world traffic video sequences demonstrate that our method is simple, robust and efficient under traffic scenes with different lighting conditions. Accurate positioning of target vehicles is thus achieved even in the presence of cast shadows.postprin

Generalized motion and edge adaptive interpolation de-interlacing algorithm

This paper presents a generalized motion and edge adaptive de-interlacing framework, which offers a structured way to develop de-interlacing algorithm. The framework encompasses many typical de-interlacing algorithms, ranging from simple interpolation based algorithms, to more complex edge dependent and motion adaptive algorithms. Based on this framework, we develop a new de-interlacing algorithm which is efficient and artifacts-free. The proposed algorithm was evaluated by five video sequences, namely, "Akiyo", Mother and Daughter", "Silent", "Foreman" and "Stefan". Experimental results confirm that the proposed algorithm performs, both objectively and subjectively, much better than other similar algorithms. These promising results indicate that the proposed framework has good potential for realizing even better de-interlacing algorithms.postprin

Watershed segmentation with boundary curvature ratio based merging criterion

This paper proposes to incorporate boundary curvature ratio, region homogeneity and boundary smoothness into a single new merging criterion to improve the oversegmentation of marker-controlled watershed segmentation algorithm. The result is a more refined segmentation result with smooth boundaries and regular shapes. To pursue a final segmentation result with higher inter-variance and lower intra-variance, an optimal number of segments could be self-determined by a proposed formula. Experimental results are presented to demonstrate the merits of this method.postprintThe 9th IASTED International Conference on Signal and Image Processing (SIP 2007), Honolulu, HI., 20-22 August 2007. In Proceedings of SIP, 2007, p. 7-1

Association of ICAM3 genetic variant with severe acute respiratory syndrome

Genetic polymorphisms have been demonstrated to be associated with vulnerability to human infection. ICAM3, an intercellular adhesion molecule important for T cell activation, and FCER2 (CD23), an immune response gene, both located on chromosome 19p13.3, were investigated for host genetic susceptibility and association with clinical outcome. A case-control study based on 817 patients with confirmed severe acute respiratory syndrome (SARS), 307 health care worker control subjects, 290 outpatient control subjects, and 309 household control subjects unaffected by SARS from Hong Kong was conducted to test for genetic association. No significant association to susceptibility to SARS infection caused by the novel coronavirus (SARS-CoV) was found for the FCER2 and the ICAM3 single nucleotide polymorphisms. However, patients with SARS homozygous for ICAM3 Gly143 showed significant association with higher lactate dehydrogenase levels (P = .0067; odds ratio [OR], 4.31 [95% confidence interval {CI}, 1.37-13.56]) and lower total white blood cell counts (P = .022; OR, 0.30 [95% CI, 0.10-0.89]) on admission. These findings support the role of ICAM3 in the immunopathogenesis of SARS. © 2007 by the Infectious Diseases Society of America. All rights reserved.published_or_final_versio

Copy number variation in Hong Kong patients with autism spectrum disorder

Oral Free Paper Session: Oral Presentation 6 [best oral presentation]BACKGROUND AND AIMS: When offering chromosomal microarray for patients with autism spectrum disorder (ASD), as according to international standards, copy number variations of uncertain significance (CNV VUS) are frequently identified, which leads to challenges in genetic counselling. We aim to study the CNV findings in children with ASD in Hong Kong, and to gather information for reclassification of recurrent CNV VUS. METHODS: ASD patients from the Department of Paediatrics and Adolescent Medicine QMH/HKU were recruited if their Array Comparative Genomic Hybridization (aCGH) were done anytime from January 2011 to August 2014 in Prenatal Diagnostic Laboratory, Tsan Yuk Hospital. Diagnosis of ASD was made by developmental paediatricians and clinical psychologists using the criteria from Diagnostic and Statistical Manual of Mental Disorders, Fourth or Fifth Edition. NimbleGen CGX-135k oligonucleotide array and Agilent CGX 60k oligonucleotide array were used. Information was summarised from the literature and existing databases to re-classify CNV VUS occurring in our ASD cohort. RESULTS: Among 288 patients with ASD in our cohort, we identified 5 patients with pathogenic CNV (1.74%) and 5 patients with likely pathogenic CNV (1.74%). Among all the CNV VUS, one variant overlapping DPP10 (hg[19] chr2:116,534,689-116,672,358) was recurrently found in Chinese individuals. The frequency of this variant in our ASD cohort was 0.35% (1 in 288), and 0.96% (9 in 935) in our controls. (P=0.467, two-tailed Fisher’s exact test). Similar CNVs were suggested to be ASD-related in previous studies recruiting mainly Caucasians. However, there were Chinese individuals with typical development possessing similar CNVs identified in independent sources (9 from our internal database, 1 from Singapore Genome Variation Project, 24 from The Singapore Prospective Study Program). CONCLUSIONS: Our study explored the CNV findings in Hong Kong paediatric ASD patients. The CNV overlapping DPP10 may be a Chinese-related copy-number variation in Hong Kong Chinese, and we reclassified it to be likely benign in our locality. Our result emphasized the need to account for ethnicity to give the most precise interpretation of aCGH data.published_or_final_versio

Human face tracking system with multiple non-overlapping cameras

A novel human face tracking system with multiple cameras is proposed in this article. Unlike most surveillance approaches requiring overlapping field of views (FOVs) for tracking targets across multiple cameras, our proposed system utilizes face recognition as cue to build correspondence between cameras, and is therefore compatible with application with non-overlapping FOVs. Face recognition achieves great success in recent years, however it has an intrinsic limitation of low tolerance to face pose changes. In the proposed system, face reconstruction technology is adopted to transform non-frontal human face to a frontal one to substantially enhance the usability of face recognition, so that correspondence of humans across multiple trajectories can be reliably established. © 2011 AICIT.link_to_subscribed_fulltex

Motion estimation method for blurred videos and application of deblurring with spatially varying blur kernels

Optical flow methods, such as Lucas-Kanade and Horn-Schunck algorithms, are popular in motion estimation. However, they fall short on accuracy when they are applied to blurred videos. Some people utilize hybrid camera system to get a low resolution image to suppress the blurring effect so that more accurate optical flow for blurred high resolution image can be further derived, though in most of the practical environments it may not be feasible to deploy hybrid camera systems from cost perspective. In this paper, we propose a novel approach to estimate motion from a blurred video without the use of hybrid camera system, and to reduce motion blur by calculating its spatially varying blur kernels. Essentially, we first separate moving objects into small regions and use the corners of their boundaries as feature points, and then apply Hierarchical Block Matching Algorithm (HBMA) to track them between frames. Motions of non-corner pixels can therefore be estimated by interpolating the motion of these corner points, which further support the calculation of the spatially varying blur kernels for deblurring purpose. Experimental results demonstrate the effectiveness of proposed method.link_to_subscribed_fulltex