Document interpretation applied to utility maps

Electrical Engineering, Mathematics and Computer Scienc

A Comparison of Human and Machine Learning-based Accuracy for Valence Classification of Subjects in Video Fragments

Facial expressions are the primary way to show one’s emotional state. Automatic recognition of these cues from video using software allows for various improvements in human-computer interaction, ranging from improved feedback for recommender systems to automatic labeling of movies according to the emotions they induce. A number of affective display databases have been created to aid development in this field. These datasets are frequently available for academic use [1, 2, 3], use picture or video stimuli and range from highly controlled [1, 2] to more natural settings [3]. We observe that methods using these datasets report accuracy figures that leave room for improvement [5]

Using Polarization features of visible light for automatic landmine detection

This chapter describes the usage of polarization features of visible light for automatic landmine detection. The first section gives an introduction to land-mine detection and the usage of camera systems. In section 2 detection concepts and methods that use polarization features are described. Section 3 describes how these detection concepts have been tested and evaluated. The results of these tests are given in section 4. Conclusions from these results are given in section 5

Local Adaptive Contrast Enhancement for Color Images

A camera or display usually has a smaller dynamic range than the human eye. For this reason, objects thatcan be detected by the naked eye may not be visible in recorded images. Lighting is here an important factor; improper local lighting impairs visibility of details or even entire objects. When a human is observing a scene with different kinds of lighting, such as shadows, he will need to see details in both the dark and light parts of the scene. For grey value images such as IR imagery, algorithms have been developed in which the local contrast of the image is enhanced using local adaptive techniques. In this paper, we present how such algorithms can be adapted so that details in color images are enhanced while color information is retained. We propose to apply the contrast enhancement on color images by applying a grey value contrast enhancement algorithm to the luminance channel of the color signal. The color coordinates of the signal will remain the same. Care is taken that the saturation change is not too high. Gamut mapping is performed so that the output can be displayed on a monitor. The proposed technique can for instance be used by operators monitoring movements of people in order to detect suspicious behavior. To do this effectively, specific individuals should both be easy to recognize and track. This requires optimal local contrast, and is sometimes much helped by color when tracking a person with colored clothes. In such applications, enhanced local contrast in color images leads to more effective monitorin

Automatic Statistics Extraction for Amateur Soccer Videos

Amateur soccer statistics have interesting applications such as providing insights to improve team performance, individual coaching, monitoring team progress and personal or team entertainment. Professional soccer statistics are extracted with labor intensive expensive manual effort which is not realistic for amateur matches. In this paper we develop a solution that automatically extracts action-related soccer statistics from a static camera pointed at the pitch. We implement a solution to player localization and action classification problem in human action recognition. Our method does not rely on player tracking, sliding windows, super voxels or construction of multiple hypotheses. Our work is developed with actual application in mind and a fully functional recognition pipeline is implemented, specifically tailored to meet the inherent challenges of action-rich soccer video

LOTUS field demonstration in Bosnia of an integrated, multi-sensor, mine-detection system for humanitarian de-mining

In this paper we report on the successful field infrared demonstrations of the LOTUS landmine detection system for humanitarian de-mining that took place in August 2002 near the village of Vidovice, in the Northeast of Bosnia and Herzegovina