Abstract: An angle adjustment apparatus includes a first connector, a second connector, a first adjusting member, a second adjusting member, and a third adjusting member. The third end of the second connector is rotatably connected to the first end of the first connector through a pivot shaft. The first adjusting member is connected to the second end of the first connector. The second adjusting member is connected to the fourth end of the second connector. The third adjusting member is configured to adjust a distance between the second end of the first connector and the fourth end of the second connector. At least one of the first adjusting member and the second adjusting member is rotatably connected to the first connector corresponding thereto or the second connector corresponding thereto, and a rotation axis for the rotatable connection is parallel to the pivot shaft.

Abstract: An angle adjustment apparatus includes a first connector, a second connector, a first adjusting member, a second adjusting member, and a third adjusting member. The third end of the second connector is rotatably connected to the first end of the first connector through a pivot shaft. The first adjusting member is connected to the second end of the first connector. The second adjusting member is connected to the fourth end of the second connector. The third adjusting member is configured to adjust a distance between the second end of the first connector and the fourth end of the second connector. At least one of the first adjusting member and the second adjusting member is rotatably connected to the first connector corresponding thereto or the second connector corresponding thereto, and a rotation axis for the rotatable connection is parallel to the pivot shaft.

Abstract: A video quality objective assessment method based on a spatiotemporal domain structure firstly combines a spatiotemporal domain gradient magnitude and color information for calculating a spatiotemporal domain local similarity, and then uses variance fusion for spatial domain fusion. The spatiotemporal domain local similarity is fused into frame-level objective quality value, and then a temporal domain fusion model is established by simulating three important global temporal effects, which are a smoothing effect, an asymmetric track effects and a recency effect, of a human visual system. Finally, the objective quality values of the distorted video sequence are obtained. By modeling the human visual temporal domain effect, the temporal domain weighting method of the present invention is able to accurately and efficiently evaluate the objective quality of the distorted video.

Abstract: A video quality objective assessment method based on a spatiotemporal domain structure firstly combines a spatiotemporal domain gradient magnitude and color information for calculating a spatiotemporal domain local similarity, and then uses variance fusion for spatial domain fusion. The spatiotemporal domain local similarity is fused into frame-level objective quality value, and then a temporal domain fusion model is established by simulating three important global temporal effects, which are a smoothing effect, an asymmetric track effects and a recency effect, of a human visual system. Finally, the objective quality values of the distorted video sequence are obtained. By modeling the human visual temporal domain effect, the temporal domain weighting method of the present invention is able to accurately and efficiently evaluate the objective quality of the distorted video.