Fig. 1. Algorithm flow chart

Fig. 2. Response map based on spectral residual visual saliency. (a) Initialized target map; (b) Spectral residual response map; (c) Three-dimensional map of spectral residual response

Fig. 3. Illustration of image texture detail. (a) Binary image of Canny edge; (b) Gradient direction amplitude map; (c) Edge direction dispersion map; (d) Three-dimensional map of edge direction dispersion

Fig. 4. Illustration of joint suitable-matching confidence map based on multi-feature fusion. (a) Joint suitable-matching confidence map; (b) Three- dimensional map of joint suitable-matching confidence

Fig. 5. Result of automatic parts selection

Fig. 6. Experimental results of proposed method on OTB100 dataset. (a) Results of automatic parts selection on sequence Carscale; (b) Results of automatic parts selection on sequence Dancer2

Fig. 6. [in Chinese]

Fig. 7. Experimental results of proposed method on FLIR Thermal dataset. (a) Results of automatic parts selection on the infrared target #1; (b) Results of automatic parts selection on infrared target #2

Fig. 8. Experimental results of proposed method on private infrared sequences. (a) Results of automatic parts selection on the private infrared sequence #1; (b) Results of automatic parts selection on the private infrared sequence #2

Fig. 9. Distance precision and overlap success rate curves of different algorithms under deformation and occlusion attribute. (a) Distance precision curve of deformation attribute; (b) Overlap success rate curve of deformation attribute; (c) Distance precision curve of occlusion attribute; (d) Overlap success rate curve of deformation attribute

Fig. 10. Frame-by-frame center location errors of parts from proposed in the paper and manual selection in different sequences

Table 1. Principle of adaptive selection of parts

Table 2. Mean center location error in different sequences