Multiscale space vehicle component identification

Vision based vehicle recognition systems have an important role in traffic surveillance. Most of these systems however fail to distinguish vehicles with similar dimensions due to the lack of other details. This paper presents a new scale space method for identifying components of moving vehicles to enable recognition eventually. In the proposed method, vehicles are first divided into multiscale regions based on the center of gravity of the foreground vehicle mask. It utilizes both the texture scale space and the intensity scale space to determine regions that are homogenous in texture and intensity, from which vehicle components are identified based on the relations between these regions. This method was tested on over a hundred outdoor traffic images and the results are very promising.published_or_final_versio

A method for vehicle count in the presence of multiple-vehicle occlusions in traffic images

This paper proposes a novel method for accurately counting the number of vehicles that are involved in multiple-vehicle occlusions, based on the resolvability of each occluded vehicle, as seen in a monocular traffic image sequence. Assuming that the occluded vehicles are segmented from the road background by a previously proposed vehicle segmentation method and that a deformable model is geometrically fitted onto the occluded vehicles, the proposed method first deduces the number of vertices per individual vehicle from the camera configuration. Second, a contour description model is utilized to describe the direction of the contour segments with respect to its vanishing points, from which individual contour description and vehicle count are determined. Third, it assigns a resolvability index to each occluded vehicle based on a resolvability model, from which each occluded vehicle model is resolved and the vehicle dimension is measured. The proposed method has been tested on 267 sets of real-world monocular traffic images containing 3074 vehicles with multiple-vehicle occlusions and is found to be 100% accurate in calculating vehicle count, in comparison with human inspection. By comparing the estimated dimensions of the resolved generalized deformable model of the vehicle with the actual dimensions published by the manufacturers, the root-mean-square error for width, length, and height estimations are found to be 48, 279, and 76 mm, respectively. © 2007 IEEE.published_or_final_versio

Highly accurate texture-based vehicle segmentation method

In modern traffic surveillance, computer vision methods have often been employed to detect vehicles of interest because of the rich information content contained in an image. Segmentation of moving vehicles using image processing and analysis algorithms has been an important research topic in the past decade. However, segmentation results are strongly affected by two issues: moving cast shadows and reflective regions, both of which reduce accuracy and require postprocessing to alleviate the degradation. We propose an efficient and highly accurate texture-based method for extracting the boundary of vehicles from the stationary background that is free from the effect of moving cast shadows and reflective regions. The segmentation method utilizes the differences in textural property between the road, vehicle cast shadow, reflection on the vehicle, and the vehicle itself, rather than just the intensity differences between them. By further combining the luminance and chrominance properties into an OR map, a number of foreground vehicle masks are constructed through a series of morphological operations, where each mask describes the outline of a moving vehicle. The proposed method has been tested on real-world traffic image sequences and achieved an average error rate of 3.44% for 50 tested vehicle images. © 2004 Society of Photo-Optical Instrumentation Engineers.published_or_final_versio

Vehicle-component identification based on multiscale textural couriers

This paper presents a novel method for identifying vehicle components in a monocular traffic image sequence. In the proposed method, the vehicles are first divided into multiscale regions based on the center of gravity of the foreground vehicle mask and the calibrated-camera parameters. With these multiscale regions, textural couriers are generated based on the localized variances of the foreground vehicle image. A new scale-space model is subsequently created based on the textural couriers to provide a topological structure of the vehicle. In this model, key feature points of the vehicle can significantly be described based on the topological structure to determine the regions that are homogenous in texture from which vehicle components can be identified by segmenting the key feature points. Since no motion information is required in order to segment the vehicles prior to recognition, the proposed system can be used in situations where extensive observation time is not available or motion information is unreliable. This novel method can be used in real-world systems such as vehicle-shape reconstruction, vehicle classification, and vehicle recognition. This method was demonstrated and tested on 200 different vehicle samples captured in routine outdoor traffic images and achieved an average error rate of 6.8% with a variety of vehicles and traffic scenes. © 2006 IEEE.published_or_final_versio

A novel method for handling vehicle occlusion in visual traffic surveillance

This paper presents a novel algorithm for handling occlusion in visual traffic surveillance (VTS) by geometrically splitting the model that has been fitted onto the composite binary vehicle mask of two occluded vehicles. The proposed algorithm consists of a critical points detection step, a critical points clustering step and a model partition step using the vanishing point of the road. The critical points detection step detects the major critical points on the contour of the binary vehicle mask. The critical points clustering step selects the best critical points among the detected critical points as the reference points for the model partition. The model partition step partitions the model by exploiting the information of the vanishing point of the road and the selected critical points. The proposed algorithm was tested on a number of real traffic image sequences, and has demonstrated that it can successfully partition the model that has been fitted onto two occluded vehicles. To evaluate the accuracy, the dimensions of each individual vehicle are estimated based on the partitioned model. The estimation accuracies in vehicle width, length and height are 95.5%, 93.4% and 97.7% respectively.published_or_final_versio

(Dis)connections between specific language impairment and dyslexia in Chinese

Poster Session: no. 26P.40Specific language impairment (SLI) and dyslexia describe language-learning impairments that occur in the absence of a sensory, cognitive, or psychosocial impairment. SLI is primarily defined by an impairment in oral language, and dyslexia by a deficit in the reading of written words. SLI and dyslexia co-occur in school-age children learning English, with rates ranging from 17% to 75%. For children learning Chinese, SLI and dyslexia also co-occur. Wong et al. (2010) first reported on the presence of dyslexia in a clinical sample of 6- to 11-year-old school-age children with SLI. The study compared the reading-related cognitive skills of children with SLI and dyslexia (SLI-D) with 2 groups of children …postprin

An Efficient Alignment Algorithm for Searching Simple Pseudoknots over Long Genomic Sequence

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Reading comprehension and its component skills in children with SLI and children with dyslexia

Poster session 1: LiteracyThe Poster Abstract Book can be viewed at: http://www.iascl2014.org/files/6014/0483/0776/Posters_Final.pdfReading comprehension involves word decoding and oral language comprehension (Hoover and Gough, 1990). Young readers with dyslexia are at risk for reading-comprehension impairment. Reading-comprehension impairment also happens in children without wordreading deficits, and about 30% of these children is language-impaired. Reading comprehension involves higher-order skills of working memory, inferencing, and comprehension monitoring (Cain & Oakhill, 2007). This study aims to examine whether Chinese children with specific language impairment (SLI) and children with dyslexia demonstrate difficulties in these skills. Ninety-five eight-year-old Primary 2 children participated in this study. Using normreferenced measures, these children were diagnosed as either normal (n=42), SLI (n=28), dyslexia (N=10), or SLI-dyslexia (n=19) at the end of Primary 1. The children completed tasks examining word reading, reading comprehension, written grammar, working memory, comprehension monitoring and literal and inferential reading comprehension of texts in which word and grammar levels were controlled. Age and Ravens were used as covariates in all MANOVA and ANOVA analyses. In both word reading and reading comprehension, the normal group outperformed the three atypical groups and the SLI group scored higher than the dyslexic group. In word reading, the SLI and the dyslexia group performed better than the co-morbid group, and in reading comprehension, only the SLI group performed better than the co-morbid group. For written grammar, the normal group again performed better than the three atypical groups, and the SLI and dyslexia group outperformed the co-morbid group. For literal and inferential comprehension, the normal group performed better than the SLI and co-morbid group, and the same pattern of results was found for comprehension monitoring and working memory. The dyslexia group did not perform worse than the normal group in these higher-order skills. These results suggest different focus of reading comprehension intervention for children with SLI and children with dyslexia. (Project funded by Hong Kong RGC755110) Hoover, W. A. & Gough, P. B. (1990). The simple view of reading. Reading and Writing, 2, 127-160. Oakhill, J. V., & Cain, K. (2004). The development of comprehension skills. In T. Nunes & P. Bryant (eds). Handbook of children’s literacy, 155-180.published_or_final_versio

(Dis)connections between specific language impairment and dyslexia in Chinese

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