Rejection-Cascade of Gaussians: Real-time adaptive background subtraction framework

Background-Foreground classification is a well-studied problem in computer vision. Due to the pixel-wise nature of modeling and processing in the algorithm, it is usually difficult to satisfy real-time constraints. There is a trade-off between the speed (because of model complexity) and accuracy. Inspired by the rejection cascade of Viola-Jones classifier, we decompose the Gaussian Mixture Model (GMM) into an adaptive cascade of Gaussians(CoG). We achieve a good improvement in speed without compromising the accuracy with respect to the baseline GMM model. We demonstrate a speed-up factor of 4-5x and 17 percent average improvement in accuracy over Wallflowers surveillance datasets. The CoG is then demonstrated to over the latent space representation of images of a convolutional variational autoencoder(VAE). We provide initial results over CDW-2014 dataset, which could speed up background subtraction for deep architectures.Comment: Accepted for National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG 2019

The Discovery of Cometary Activity in Near-Earth Asteroid (3552) Don Quixote

The near-Earth object (NEO) population, which mainly consists of fragments from collisions between asteroids in the main asteroid belt, is thought to include contributions from short-period comets as well. One of the most promising NEO candidates for a cometary origin is near-Earth asteroid (3552) Don Quixote, which has never been reported to show activity. Here we present the discovery of cometary activity in Don Quixote based on thermal-infrared observations made with the Spitzer Space Telescope in its 3.6 and 4.5 {\mu}m bands. Our observations clearly show the presence of a coma and a tail in the 4.5 {\mu}m but not in the 3.6 {\mu}m band, which is consistent with molecular band emission from CO2. Thermal modeling of the combined photometric data on Don Quixote reveals a diameter of 18.4 (-0.4/+0.3) km and an albedo of 0.03 (-0.01/+0.02), which confirms Don Quixote to be the third-largest known NEO. We derive an upper limit on the dust production rate of 1.9 kg s^-1 and derive a CO2 gas production rate of (1.1+-0.1)10^26 molecules s^-1. Spitzer IRS spectroscopic observations indicate the presence of fine-grained silicates, perhaps pyroxene rich, on the surface of Don Quixote. Our discovery suggests that CO2 can be present in near-Earth space over a long time. The presence of CO2 might also explain that Don Quixote's cometary nature remained hidden for nearly three decades.Comment: 40 pages, 8 figures, accepted by Ap

A generic framework for video understanding applied to group behavior recognition

This paper presents an approach to detect and track groups of people in video-surveillance applications, and to automatically recognize their behavior. This method keeps track of individuals moving together by maintaining a spacial and temporal group coherence. First, people are individually detected and tracked. Second, their trajectories are analyzed over a temporal window and clustered using the Mean-Shift algorithm. A coherence value describes how well a set of people can be described as a group. Furthermore, we propose a formal event description language. The group events recognition approach is successfully validated on 4 camera views from 3 datasets: an airport, a subway, a shopping center corridor and an entrance hall.Comment: (20/03/2012