[PDF] Top 20 Feature Descriptor for Crowd Density Estimation

... Crowd density estimation is an important task for crowd ...estimating crowd density from images and ...texture feature-based approach for the estimation of ... See full document

... high density fields and complex background when it comes to pixel statistics and texture analysis ...into feature extraction and feature classification. Feature extraction includes the frame ... See full document

... of crowd anomalies from surveillance CCTVs is a research-intensive and application-demanding ...detecting crowd abnormalities through analyzing the spatial and temporal features of input video ...image ... See full document

... D. Conte, et.al.was able to monitor the crowd in efficiently and in real-time [11]. Their system exhibited high precision and high speed in finding the target, and hence can be used for real-time monitoring ... See full document

... Crowd Density Analysis (CDA) aims to compute concentration of crowd in surveillance ...the crowd density using crowd feature tracking with optical ...the crowd ... See full document

... the crowd counting system appears in Figure ...into crowd regions moving in different directions, using a mixture of dynamic ...each crowd segment, various features are extracted, while applying a ... See full document

... SIFT-related feature description distinctiveness against Spin Images has been compared in ...In feature- based approaches, feature points are usually associated to descriptors, which ideally should ... See full document

... on crowd analytics, many of existing methods are problem-specific, ...scene crowd analytics with traditional and deep learning ...different crowd videos and ...to crowd density ... See full document

... In this paper, we develop three different techniques for estimating a crowd’s density in outdoor scenes. The difficulties in using outdoor scenes as input data include variation of illumination from weather and ... See full document

... pixel-based crowd density estimation system (CDES) for pictures received from at ...the crowd into five distinct batches, from very low to very ...high crowd density level ... See full document

... A second category of methods tackles this issue by incorporating appearance information as well. One work that stands out in this category is that of [19], that uses mixtures of dynamic textures to describe each 3D ... See full document

... Haar feature based head detection [7] and integral channel features [8] based head detection [9] are ...a crowd is estimated, but this method may fail if the observed area is much crowded and only a few ... See full document

... the descriptor were ...proposed descriptor is invariant to rotation and uniform ...this descriptor is weak against non-uniform scale or affine transformations ...curvature descriptor for ... See full document

... INVARIANT FEATURE DESCRIPTOR This section presents a stepwise procedure of how RIFD extracts precise features from video sequences, and utilizes l2-regularized Collaborative Representation Classifier (CRC) ... See full document

... In this work we introduced a novel technique for unsupervised forensic analysis of video file containers. To achieve the differences in the video file content defined by different manufacturers, models and software ... See full document

... ➢ Experiment II: Impact from the hierarchy level Figure 3 (a) shows the quality degradation measured for different demand levels in the three datasets. We can see that isolation include point for Label Me occurs at level ... See full document

... pathological descriptor that can be extracted from the activated neurons of a diabetic retinopathy ...and feature encoded in this descriptor, we propose a GAN based method to synthesize pathological ... See full document

... image feature representation method to describe the rich information of minority costume ...final feature vector for minority costume image is formed by effective fusion of color histogram and edge ... See full document

... (MI) estimation is an important component of several data mining tasks ...(e.g feature selection). In classification settings, MI estimation essentially depends on the estimation of the ratio ... See full document

... Invariant Feature Transform) is a well- established local feature descriptors, which was proposed in ...SIFT feature analysis is used. Due to SIFT feature descriptor is invariant to ... See full document