Rain Removal in Traffic Surveillance: Does it Matter?

Varying weather conditions, including rainfall and snowfall, are generally regarded as a challenge for computer vision algorithms. One proposed solution to the challenges induced by rain and snowfall is to artificially remove the rain from images or video using rain removal algorithms. It is the promise of these algorithms that the rain-removed image frames will improve the performance of subsequent segmentation and tracking algorithms. However, rain removal algorithms are typically evaluated on their ability to remove synthetic rain on a small subset of images. Currently, their behavior is unknown on real-world videos when integrated with a typical computer vision pipeline. In this paper, we review the existing rain removal algorithms and propose a new dataset that consists of 22 traffic surveillance sequences under a broad variety of weather conditions that all include either rain or snowfall. We propose a new evaluation protocol that evaluates the rain removal algorithms on their ability to improve the performance of subsequent segmentation, instance segmentation, and feature tracking algorithms under rain and snow. If successful, the de-rained frames of a rain removal algorithm should improve segmentation performance and increase the number of accurately tracked features. The results show that a recent single-frame-based rain removal algorithm increases the segmentation performance by 19.7% on our proposed dataset, but it eventually decreases the feature tracking performance and showed mixed results with recent instance segmentation methods. However, the best video-based rain removal algorithm improves the feature tracking accuracy by 7.72%.Comment: Published in IEEE Transactions on Intelligent Transportation System

Ensemble of Example-Dependent Cost-Sensitive Decision Trees

Several real-world classification problems are example-dependent cost-sensitive in nature, where the costs due to misclassification vary between examples and not only within classes. However, standard classification methods do not take these costs into account, and assume a constant cost of misclassification errors. In previous works, some methods that take into account the financial costs into the training of different algorithms have been proposed, with the example-dependent cost-sensitive decision tree algorithm being the one that gives the highest savings. In this paper we propose a new framework of ensembles of example-dependent cost-sensitive decision-trees. The framework consists in creating different example-dependent cost-sensitive decision trees on random subsamples of the training set, and then combining them using three different combination approaches. Moreover, we propose two new cost-sensitive combination approaches; cost-sensitive weighted voting and cost-sensitive stacking, the latter being based on the cost-sensitive logistic regression method. Finally, using five different databases, from four real-world applications: credit card fraud detection, churn modeling, credit scoring and direct marketing, we evaluate the proposed method against state-of-the-art example-dependent cost-sensitive techniques, namely, cost-proportionate sampling, Bayes minimum risk and cost-sensitive decision trees. The results show that the proposed algorithms have better results for all databases, in the sense of higher savings.Comment: 13 pages, 6 figures, Submitted for possible publicatio

The AAU Multimodal Annotation Toolboxes: Annotating Objects in Images and Videos

This tech report gives an introduction to two annotation toolboxes that enable the creation of pixel and polygon-based masks as well as bounding boxes around objects of interest. Both toolboxes support the annotation of sequential images in the RGB and thermal modalities. Each annotated object is assigned a classification tag, a unique ID, and one or more optional meta data tags. The toolboxes are written in C++ with the OpenCV and Qt libraries and are operated by using the visual interface and the extensive range of keyboard shortcuts. Pre-built binaries are available for Windows and MacOS and the tools can be built from source under Linux as well. So far, tens of thousands of frames have been annotated using the toolboxes.Comment: 6 pages, 10 figure

Point of Care Tools and Libraries: 12th Annual Health Sciences Lively Lunch

This session included a discussion about point of care tools in the health information setting. Klimley provided a presentation on the point of care tools landscape that highlighted the importance and relevance of this topic now, evaluations that have been published about these tools, funding issues, and desirable elements of the tools. The presentation included examples of marketing techniques and product advertisements to portray the various claims and testimonials regarding these products, which provided a critical discussion on the products and their use in health information settings. A lively discussion followed the presentation to allow participants to express some of their concerns about point of care tools and their role in the future. The results of the session are explained in the document

One Of A Kind Grammar: The Role Of Sentence Diversity In Children's Grammatical Development

ABSTRACT Purpose: The purpose of this study was to investigate the contribution of parent sentence diversity to children???s sentence diversity at a later age. Children???s sentence diversity was further explored to examine its contribution to children???s subsequent 3rd person tense and agreement marking. Method: Twenty parent-child dyads participated in the study. Spontaneous language samples were collected from parents when children were 21 months of age and from children at 30 months of age. These samples were coded for unique subject-verb combinations (USV), the sentence diversity measure. At 36 months of age, the Test of Early Grammatical Impairment was administered to measure children???s ability to accurately mark tense and agreement. Results: No relationship was found between parent sentence diversity and children???s sentence diversity. However, children???s 30-month sentence diversity was significantly related to their ability to mark tense and agreement at 36 months of age. Conclusion: Children???s sentence diversity is a foundation for their subsequent acquisition of tense and agreement. However, it is unclear exactly what properties of parent input support children???s early acquisition of diverse sentences

Business Location Evaluation for Advertising Partnerships

Businesses benefit from being able to arrive at an accurate valuation for the locations they own/ operate for the purposes of advertising. Such valuation can be based on the amount and composition of the traffic passing through that location. This disclosure describes techniques to construct an index for a business location by using relevant customer, geographical, and shopping data to help businesses arrive at an accurate value for the location for advertising purposes. Businesses can offer advertising at their location and choose from available locations to locate their advertisements. A marketplace for physical advertising can also be established using the described techniques

Location Selection for Flagship Retail Store

Brands benefit from greater exposure to potential consumers. One way to improve exposure is to open a flagship retail store that provides a dedicated brand experience in a new geographic area so that consumers in the region are exposed to the goods and services in person. This disclosure describes techniques to evaluate available locations to determine an appropriate location for a flagship store where the number of potential new consumers that are exposed to the brand is high. Different road segments, including indoor segments are scored based on data indicative of the number of unique and new persons that pass through the segment. Consumer preferences for various product categories are obtained and the identified road segments are ranked based on the number of consumers that match the brand and/or category. Rental costs for competing locations are evaluated to adjust the ranking and choose the store location. Once the store is operational, efficacy of store location is measured by visits, online activity, and purchases

Optimized Upload of Telemetry Data

Modern telemetry entails the gathering of data (per location or time interval) in such large quantities that the data often exceeds the capacity of the communication channels to a server (or cloud). An example of such telemetry is the gathering of street-level imagery and video where, even when the data-collecting vehicle has a wireless 4G connection, a very large amount of data is gathered so quickly that it is written on storage media such as solid state, optical, magnetic storage, etc. and physically mailed to a processing center. Besides the delay attributable to physical mailing, manual processing of the storage media at the point of capture also causes a substantial delay. This disclosure describes techniques to optimize the latency and bandwidth of sensor-acquired telemetry data by rapidly determining, e.g., at the point of capture, the value of specific pieces of data (image, sequence of video frames, etc.), and by utilizing the available communication and computational capabilities of the device to process data in the order of relative value

Contextually-Relevant Vehicle Advertising

Existing approaches to adapt advertising messages on vehicle-mounted displays based on location rely on static demographic information about the area. Such approaches do not take into account changes in relevant contextual factors connected to the current location of the vehicle at a given time. This disclosure describes techniques to automatically select and display contextually relevant messages, such as advertisements, on vehicles. The messages are dynamically updated based on relevant changes in the vehicle’s context, such as location, time of day, day of the week, people in the vicinity, local events, current advertising needs of businesses, etc. If the route of a vehicle is known in advance fully or partially, the set of messages for the route can be pre-selected. When the route for a vehicle is flexible, the techniques can be utilized to select routes based on advertising needs