Three different advanced adaptation techniques for improving the video perception of users are proposed in this paper. The proposed techniques exploit different adaptation decision-taking and adaptation approaches to adapt particular core parameters while considering diverse contextual information and constraints to achieve improved video perception of users. The first proposed technique employs a utility-based adaptation approach to perform adaptation operations on spatial resolution, frame rate, and quality scalability parameters according to the content-related contextual information (i.e., motion activity and structural feature) while fulfilling network bandwidth and terminal display size constraints. Using this technique, video contents can be adapted with the scalability parameters best fitting users' and contextual constraints' needs to achieve improved video perception. The second technique relies on prioritizing key frame, non-key frame, and temporal layer parameter-related network abstraction layer units to adapt video contents to satisfy network bandwidth constraint. The rate-distortion performances of adapted video contents can be improved by utilizing this technique in adaptation operations both in terms of bit rate of adapted video contents and video perception of users. The third technique is based on adapting the bit rate of 3-D video contents according to the changes in ambient illumination of the viewing environment. The adaptation results evaluated by either subjective or objective quality assessment techniques prove that all of the proposed techniques are efficient to improve the video perception of users.