Hamed Kiani Galoogahi

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Modern descriptors like HOG and SIFT are now commonly used in vision for pattern detection within image and video. From a signal processing perspective, this detection process can be efficiently posed as a correlation/ convolution between a multi-channel image and a multi-channel detector/filter which results in a single channel response map indicating(More)
In this paper, we propose a new face descriptor to directly match face photos and sketches of different modalities, called Local Radon Binary Pattern (LRBP). LRBP is inspired by the fact that the shape of a face photo and its corresponding sketch is similar, even when the sketch is exaggerated by an artist. Therefore, the shape of face can be exploited to(More)
Correlation filters take advantage of specific properties in the Fourier domain allowing them to be estimated efficiently: O(N D log D) in the frequency domain, versus O(D<sup>3</sup> + N D<sup>2</sup>) spatially where D is signal length, and N is the number of signals. Recent extensions to correlation filters, such as MOSSE, have reignited interest of(More)
In this paper, we address the shape classification problem by proposing a new integrating approach for shape classification that gains both local and global image representation using Histogram of Oriented Gradient (HOG). In both local and global feature extraction steps, we use PCA to make this method invariant to shapes rotation. Moreover, by using a(More)
Automatic face sketch recognition plays an important role in law enforcement. Recently, various methods have been proposed to address the problem of face sketch recognition by matching face photos and sketches, which are of different modalities. However, their performance is strongly affected by the modality difference between sketches and photos. In this(More)
Recently the histogram of oriented tracklets (HOT) was shown to be an efficient video representation for abnormality detection and achieved state-of-the-arts on the available datasets. Unlike standard video descriptors that mainly employ low level motion features, e.g. optical flow, the HOT descriptor simultaneously encodes magnitude and orientation of(More)
Face photo-sketch matching has received great attention in recent years due to its vital role in law enforcement. The major challenge of matching face photo and sketch is difference of visual characteristics between face photo and sketch which is referred as modality gap. Earlier approaches have reduced the modality gap by synthesizing face photos and(More)
Abnormal detection in crowd is a challenging vision task due to the scarcity of real-world training examples and the lack of a clear definition of abnormality. To tackle these challenges, we propose a novel measure to capture the commotion of a crowd motion for the task of abnormality detection in crowd. The unsupervised nature of the proposed measure(More)