Head Pan Research Articles

EFFECT OF GENDER ON FARMERS’ OWNERSHIP, CONTROL AND ACCESSIBILITY TO CLIMATE CHANGE ADAPTATION RESOURCES IN SOUTHWEST NIGERIA

The ability to access, control and own adaptation resources is a critical factor in determining rural farmers’ adaptive potential and decision-making towards adaptation to climate change. This study investigated the effect of gender on farmers’ accessibility, control and ownership of climate change adaptation resources in Ogun and Ekiti States respectively, Nigeria. Three hundred and fifty eighty men (358) and (222) women farmers were randomly selected through a multi-stage sampling procedure. A pre-tested questionnaire was used to obtain data and analysed with frequency counts, means, percentages, Chi-square. A positive and statistically significant association (P<0.05) existed between the gender of the respondents and their accessibility to adaptation resources, like hoe (χ2= 10.137), wheelbarrow (χ2=5.647), digger (χ2=11.982), sprayers (χ2=11.792), head pan (χ2=9.5599), education (χ2=22.359), grass plant (χ2=9..912), health-care (χ2=13.764), pesticides (χ2=6.391) inorganic fertilizer (χ2=7.876), transportation means (χ2=10.897), average annual income (χ2= 8.026), labour (χ2=12 .557), information (χ2=12.557), and medicinal plants (χ2=11.296). There existed a positive and statistically significant association (P<0.05) between the gender of the farmers and their control of adaptation resources like digger (χ2=14.630), sprayer (χ2=6.631), head pan (χ2=4.811), education (χ2=11.657) transportation (χ2=3.364) and average annual income (χ2=33.013). Also, there existed a positive and significant association (P<0.05) between the gender of the farmers and their ownership of adaptation resources like land (χ2=6.815), water (χ2-4.491), health-care (χ2= 2.088), labour (χ2= 5.992) and sources of information of climate change (χ2=3.595). As a result, gender-responsive intervention is necessary to strengthen men and women farmers' climate resilience and improve their adaptation capabilities through access to

A new approach to wire-frame tracking for semantic model-based moving image coding

Automatic wire-frame fitting and automatic wire-frame tracking are the two most important and most difficult issues associated with semantic-based moving image coding. A novel approach to high-speed tracking of important facial features is presented as a part of a complete fitting-tracking system we have developed. The method allows real-time processing of head-and-shoulders sequences using software tools only. The algorithm is based on eigenvalue decomposition of the sub-images extracted from subsequent frames of the video sequence. Since each facial feature (the left eye, the right eye, the nose and the lips) is tracked separately, the algorithm can be easily adapted for a parellel machine. The algorithm was tested on numerous widely used head-and-shoulders video sequences containing speaker's head pan, rotation and zoom with remarkably good results. The experiments we have carried out prove that it is possible to maintain tracking even when the facial features are partially occluded.

Facial Motion Analysis for Content-based Video Coding

Automatic wire-frame fitting and automatic wire-frame tracking are the two most important and most difficult issues associated with semantic-based moving image coding. A novel approach to high speed tracking of important facial features is presented as a part of a complete fitting-tracking system. The method allows real-time processing ofhead-and-shoulders sequences using software tools only. The algorithm is based on eigenvalue decomposition of the sub-images extracted from subsequent frames of the video sequence. Each important facial feature (the left eye, the right eye, the nose and the lips) is tracked separately using the same method. The algorithm was tested on widely used head-and-shoulders video sequences containing the speaker's head pan, rotation and zoom with remarkably good results. These experiments prove that it is possible to maintain tracking even when the facial features are partially occluded.

Tracking of the motion of important facial features in model-based coding

A new method of tracking the position of important facial features for semantic wire-frame-based moving-image coding is presented. Reliable and fast tracking of the facial features in head-and-shoulders scenes is of paramount importance for reconstruction of the speaker's motion in videophone systems if wire-frame-based coding is used. The proposed method is based on eigenvalue decomposition of the sub-images extracted from subsequent frames of the video sequence. Motion of each facial feature (the left eye, the right eye, the nose and the lips) is tracked separately. No restrictions other than the presence of the speaker's face, were imposed on the actual contents of the scene. The algorithm was tested on widely used head-and-shoulders video sequences containing moderate head pan, rotation and zoom with remarkably good results. Tracking was maintained even when the facial features were occluded. The algorithm can also be used in other semantic-based systems.

Reliable tracking of facial features in semantic-based video coding

A new method of tracking the position of important facial features for semantic-based moving image coding is presented. Reliable and fast tracking of the facial features in head-and-shoulders scenes is of paramount importance for reconstruction of the speaker's motion in videophone systems. The proposed method is based on eigenvalue decomposition of the sub-images extracted from subsequent frames of the video sequence. Motion of each facial feature (the left eye, the right eye, the nose and the lips) is tracked separately; this means that the algorithm can be easily adapted for a parallel machine. No restrictions, other than the presence of the speaker's face, were imposed on the actual contents of the scene. The algorithm was tested on numerous widely used head-and-shoulders video sequences containing moderate head pan, rotation and zoom, with remarkably good results. Tracking was maintained even when the facial features were occluded. The algorithm can also be used in other semantic-based systems.