faces, hands, bodies, cats, dogs, surfaces, objects, etc.), tracking of such objects as they leave, enter, and move around the field of view in video frames, and the modification or transformation of
However, counting in dense scenes still faces numerous challenges. Highly crowded scenes present irregular object distributions and uneven object scales. Traditional convolutional neural networks struggle with fixed-size kernels for feature extraction, limiting counting performance. The current approaches ...
Figure 1illustrates the methodology. First, multiple Gabor filters are defined. Thirty-six different orientations and seven wavelengths were set, and 252 filtered images were generated. Each filtered image shows how much of the nanoparticle contains faces in a particular orientation. A feature vector...
However, crowd density estimation still faces some serious challenges. Figure 1. (a) Pedestrian Street. (b) Festival celebration. (c) Sports event. (d) Tourist attraction. Crowd estimation is easily affected by the perspective effect of the camera; the feature vector will change as the ...